Accuracy Of Image Interpretation Research Articles

Thin Cloud Removal for Multispectral Remote Sensing Images Using Convolutional Neural Networks Combined With an Imaging Model

Multispectral remote sensing images are often degraded by clouds, resulting in the reduced efficiency and accuracy of image interpretation. Thin cloud removal is one of the most important and significant tasks for optical multispectral images. In this article, we propose a novel thin cloud removal method for multispectral images, which is a combination of traditional methods and deep learning methods. First, we adopt U-Net to estimate the reference thin cloud thickness map of the cloudy image. Then, a convolutional neural network named Slope-Net is designed to estimate the thickness coefficient of each band relative to the reference thin cloud thickness map to obtain the thin cloud thickness maps of different bands. Finally, the recovered clear image can be obtained by subtracting the thin cloud thickness maps from the cloudy image according to the traditional thin cloud imaging model. To train U-Net and Slope-Net, a wavelength-dependent thin cloud simulation method is presented to generate a labeled dataset composed of synthetic cloudy images, corresponding clear images, reference thin cloud thickness maps, and thickness coefficients. Qualitative and quantitative comparison experiments are conducted on both synthetic cloudy images and real cloudy images from the Landsat 8 Operational Land Imager. The results indicate that the proposed method can effectively remove thin clouds in multispectral images with various land cover types and maintain good color fidelity.

RFI Suppression for SAR Systems Based on Removed Spectrum Iterative Adaptive Approach

A synthetic aperture radar (SAR) system can be seriously contaminated by radio frequency systems because of working in the same microwave frequency bands, which would degrade the SAR image quality and affect the accuracy of image interpretation. In this paper, a novel radio frequency interference (RFI) suppression approach including RFI identification, band-stop filtering and a removed spectrum iterative adaptive approach (RSIAA) is proposed. First, the smoothing process is added before RFI signal detection to improve the RFI detection capacity. Afterwards, the band-stop filtering with a broaden factor is proposed to mitigate the residual RFI, and it ensures the accuracy of the following removed spectrum recovery by the RSIAA. Finally, the removed spectrum components are estimated from available adjacent spectrum data by the RSIAA in turn to obtain the desired range spectra. Compared with the conventional range frequency filtering method for RFI suppression, the capacity of the weak RFI signal detection is improved, and the increased sidelobes due to the discontinuous spectra are well suppressed. Simulation experiments on both simulated SAR raw data, Gaofen-3 and Sentinel-1 SAR raw data validate the proposed RFI suppression approach.

Validation of a Novel Cutaneous Neoplasm Diagnostic Self-Efficacy Instrument (CNDSEI) for Evaluating User-Perceived Confidence With Dermoscopy.

Accurate medical image interpretation is an essential proficiency for multiple medical specialties, including dermatologists and primary care providers. A dermatoscope, a ×10-×20 magnifying lens paired with a light source, enables enhanced visualization of skin cancer structures beyond standard visual inspection. Skilled interpretation of dermoscopic images improves diagnostic accuracy for skin cancer. Design and validation of Cutaneous Neoplasm Diagnostic Self-Efficacy Instrument (CNDSEI)-a new tool to assess dermatology residents' confidence in dermoscopic diagnosis of skin tumors. In the 2018-2019 academic year, the authors administered the CNDSEI and the Long Dermoscopy Assessment (LDA), to measure dermoscopic image interpretation accuracy, to residents in 9 dermatology residency programs prior to dermoscopy educational intervention exposure. The authors conducted CNDSEI item analysis with inspection of response distribution histograms, assessed internal reliability using Cronbach's coefficient alpha (α) and construct validity by comparing baseline CNDSEI and LDA results for corresponding lesions with one-way analysis of variance (ANOVA). At baseline, residents respectively demonstrated significantly higher and lower CNDSEI scores for correctly and incorrectly diagnosed lesions on the LDA (P = 0.001). The internal consistency reliability of CNDSEI responses for the majority (13/15) of the lesion types was excellent (α ≥ 0.9) or good (0.8≥ α <0.9). The CNDSEI pilot established that the tool reliably measures user dermoscopic image interpretation confidence and that self-efficacy correlates with diagnostic accuracy. Precise alignment of medical image diagnostic performance and the self-efficacy instrument content offers opportunity for construct validation of novel medical image interpretation self-efficacy instruments.

Accuracy of radiographer comment following a two-month experiential and blended learning in appendicular skeleton X-ray interpretation: The Singapore experience

IntroductionThe value of combined blended and experiential learning on radiographer diagnostic comment has not been explored. This study aims to examine the accuracy of image interpretation comment of radiographers who received a period of blended and experiential learning in Radiographer Abnormality Detection Systems (RADS). MethodsWe evaluated the diagnostic opinions of 13 radiographers who received a blended training and experiential learning (a process of self-learning and reflection) in RADS. Radiographers' opinions on 16,483 images were examined using the final radiologists’ report as a reference standard. For each radiographer, we recorded the number of true positive, true negative, false positive and false negative opinions and MedCal® was used to calculate diagnostic performance and error rates. A t-test was used to assess whether the number of images read was associated with performance and whether the radiographers retained performance over time. ResultsSensitivity ranged from 87.4 (84.0–90.2) to 98.9 (97.5–99.7) with a mean of 94.3 (93.6–94.8). Specificity varied from 96.4 (94.8–97.5) to 99.9 (99.41–100.0) with a mean of 98.2 (97.9–98.4). Diagnostic accuracy ranged from 93.1 (91.5–94.4) to 99.5 (98.9–99.8) with a mean of 96.9 (96.6–97.1). The mean false positive rate was 0.018 (range: 0.010–0.031) with a false negative rate of 0.057 (range: 0.026–0.11). There were no differences in performance between the first and latter nine months of providing opinions and the number of images reviewed was not associated with performance. ConclusionRadiographers who received blended and experiential learning in RADS provide accurate diagnostic comments on plain emergency appendicular skeleton radiographs. Implication for practiceA combined blended and experiential learning can equip radiographers to provide diagnostic opinion on plain appendicular skeleton radiographs.

A think-aloud study to inform the design of radiograph interpretation practice

Models for diagnostic reasoning in radiology have been based on the observed behaviors of experienced radiologists but have not directly focused on the thought processes of novices as they improve their accuracy of image interpretation. By collecting think-aloud verbal reports, the current study was designed to investigate differences in specific thought processes between medical students (novices) as they learn and radiologists (experts), so that we can better design future instructional environments. Seven medical students and four physicians with radiology training were asked to interpret and diagnose pediatric elbow radiographs where fracture is suspected. After reporting their diagnosis of a case, they were given immediate feedback. Participants were asked to verbalize their thoughts while completing the diagnosis and while they reflected on the provided feedback. The protocol analysis of their verbalizations showed that participants used some combination of four processes to interpret the case: gestalt interpretation, purposeful search, rule application, and reasoning from a prior case. All types of processes except reasoning from a prior case were applied significantly more frequently by experts. Further, gestalt interpretation was used with higher frequency in abnormal cases while purposeful search was used more often for normal cases. Our assessment of processes could help guide the design of instructional environments with well-curated image banks and analytics to facilitate the novice’s journey to expertise in image interpretation.

Cassava Farming Based On Rural Agribusiness Development

Agriculture products need market value increases trough the development of rural agribusiness. The success of the program needs to be supported by the community to create the expansion of marketing access, the sustainability of the agribusiness and strengthening of capital so as to create savings. Community as a regional unit (natural and social), where its members (farmers and non farmers) carry out various daily activities, which are social capital to play an important role in a development process. This research had the following objectivies: a) determining the synergy of participation of each element (farmer and non farmer) in the development of rural agribusiness, b) finding solutions to the participation constraints of each agribusiness chain, and c) finding sub models of community facilities. The research was conducted in Central Java Province as a cassava-producing region and tapioca center, namely in the districts of Pati and. Meanwhile, the objects of the research included : facilitation actions for community empowerment on the job training, agriculture product processing and independent of the rural agribusiness development, community potential, and the establishment of agrbusiness microfinance institutions. There were two populations of this study, they were: area of cassava land and center of agribusiness, and community members consisting of farmers element (cassava farmers), non farmer (owner of agribusiness and workfoces of agribusiness), and off farmers (owner of transport, transport drivers). Sampling technique used in this study was cluster sampling technique to find out agribusiness data and accuracy test of the accuracy of image interpretation in determining the number of samples using the guidelines of BIG (Geographyc Information Institution in Indonesia), as well as simple random sampling technique for agribusiness center. Data analysis technique used was multiple linear regression for participatory synergistic analysis and synthesizing information to be used in formulating alternatives and policy preferenees are expressed comparatively, predicted in quantitative and qualitative languages as the basis for decision making for proverty reduction analysis. Based on the research data, the results of simple linear regression analysis result in a regression equation Y = 5.26 + 18.26X, this shows a positive influence of each variable where X represents the amount of daily cassava production and Y variable represents the number daily income, meaning that there will be an increase in participation synergy if each of these variables is increased in quantity or quantity. Meanwhile, in testing hypotheses between the two variables produces t count of 0.871, where the t table is 0.374 which means t count t table so that the conclusions obtained are the influence between variables on the magnitude of the synergy of participation from PUAP. According to the calculation of correlation analysis, the results of the calculation of simple linear regression analysis produce a correlation coefficient of 0.801 and a determination coefficient of 0.642, which means that when linked to the interpretation table the correlation coefficient for correlation between variables is in the "very strong" interval level classification (0 , 80 - 1.00). The results of the study were to increase the synergy of the participation of members of rural communities, accelerate networking between citizens or communities through social planned change known as social engineering and labor intensive agricultural processing.

Physician Barriers and Facilitators for Screening for Congenital Heart Disease With Routine Obstetric Ultrasound: A National United States Survey.

Prenatal detection of congenital heart disease with obstetric screening remains at less than 50% in most population studies, far from what is thought to be achievable. We sought to identify barriers/facilitators for screening from the perspective of interpreting physicians and to understand how these barriers/facilitators may be associated with interpretation of screening images. Our mixed-methods studies included 4 focus groups in centers across the United States with obstetric, maternal-fetal medicine, and radiology providers who interpreted obstetric ultrasound studies. Themes around barriers/facilitators for fetal heart screening were coded from transcripts. A national Web-based survey was then conducted, which quantitatively measured reported barriers/facilitators and measured physicians' ability to interpret fetal heart-screening images. Multivariable generalized linear random-effect models assessed the association between barriers/facilitators and the accuracy of image interpretation at the image level. Three main themes were identified in the focus groups: intrinsic barriers (ie, comfort with screening), external barriers (ie, lack of feedback), and organizational barriers (ie, study volumes). Among 190 physician respondents, 104 interpreted ultrasound studies. Perceptions of barriers varied by practice setting, with nontertiary providers having lower self-efficacy and perceived usefulness of cardiac screening. Facilitators associated with the odds of accurate interpretation of screening images were knowledge (odds ratio, 2.54; P = .002) and the volume of scans per week (odds ratio, 1.01 for every additional scan; P = .04). Some of the main barriers to cardiac screening identified and prioritized by physicians across the United States were knowledge of screening and minimal volumes of scans. Targeting these barriers will aid in improving prenatal detection of congenital heart disease.

Barriers to Sonographer Screening for Fetal Heart Defects: A U.S. National Survey

Objective: We surveyed obstetric sonographers, who are at the forefront of the screening process to determine how barriers to prenatal cardiac screening impacted screening abilities. Methods: We performed a cross-sectional national survey of obstetric sonographers in the United States using a sampling frame from American Registry of Diagnostic Medical Sonography mailing lists. The web survey measured the ability to obtain and interpret fetal heart images. Several cognitive, sociodemographic, and system-level factors were measured, including intention to perform cardiac imaging. Regression and mediation analyses determined factors associated with intention to perform and ability to obtain and interpret cardiac images. Subgroup analyses of sonographers in tertiary versus nontertiary centers were also performed. Results: Survey response rate either due to noncontact or nonresponse was 40%. Of 480 eligible sonographers, ~30% practiced in tertiary settings. Sonographers had lower intention to perform outflow views compared to 4 chambers. Higher self-efficacy and professional expectations predicted higher odds of intention to perform outflow views (OR 2.8, 95% CI 1.9–4.2 and 1.9, 95% CI 1.1–3.0, respectively). Overall accuracy of image interpretation was 65% (±14%). For the overall cohort and nontertiary subgroup, higher intention to perform outflows was associated with increased accuracy in overall image interpretation. For the tertiary subgroup, self-efficacy and feedback were strongly associated with accuracy. Conclusions: We identified several modifiable (some heretofore unrecognized) targets to improve prenatal cardiac screening. Priorities identified by sonographers that are associated with screening success should guide future interventions.

Pes Anserinus: Anatomy and Pathology of Native and Harvested Tendons.

OBJECTIVE. The purpose of this article is to review the anatomy and pathology of the pes anserinus to increase the accuracy of imaging interpretation of findings affecting these medial knee structures. CONCLUSION. The pes anserinus, consisting of the conjoined tendons of the sartorius, gracilis, and semitendinosus muscles and their insertions at the medial aspect of the knee, is often neglected during imaging assessment. Common pathologic conditions affecting the pes anserinus include overuse, acute trauma, iatrogenic disorders, and tumors and tumorlike lesions.

Deep Learning Applications in Chest Radiography and Computed Tomography: Current State of the Art.

Deep learning is a genre of machine learning that allows computational models to learn representations of data with multiple levels of abstraction using numerous processing layers. A distinctive feature of deep learning, compared with conventional machine learning methods, is that it can generate appropriate models for tasks directly from the raw data, removing the need for human-led feature extraction. Medical images are particularly suited for deep learning applications. Deep learning techniques have already demonstrated high performance in the detection of diabetic retinopathy on fundoscopic images and metastatic breast cancer cells on pathologic images. In radiology, deep learning has the opportunity to provide improved accuracy of image interpretation and diagnosis. Many groups are exploring the possibility of using deep learning-based applications to solve unmet clinical needs. In chest imaging, there has been a large effort to develop and apply computer-aided detection systems for the detection of lung nodules on chest radiographs and chest computed tomography. The essential limitation to computer-aided detection is an inability to learn from new information. To overcome these deficiencies, many groups have turned to deep learning approaches with promising results. In addition to nodule detection, interstitial lung disease recognition, lesion segmentation, diagnosis and patient outcomes have been addressed by deep learning approaches. The purpose of this review article was to cover the current state of the art for deep learning approaches and its limitations, and some of the potential impact on the field of radiology, with specific reference to chest imaging.

Bridging the Radiation Oncology and Diagnostic Radiology Communication Gap: A Survey to Determine Usefulness and Optimal Presentation of Radiotherapy Treatment Plans for Radiologists

Rationale and ObjectivesWe hypothesized that providing visual-spatial information to radiologists on where radiation has been delivered in an easily accessible way may improve the accuracy of image interpretation and thereby improve quality of patient care. We present a national representation of radiologists’ opinions regarding the usefulness and optimal approach for implementing a system to promote access to radiotherapy (RT) plans. MethodsAn anonymous survey was sent to the members of the Association of University Radiologists. Descriptive statistics were performed. ResultsQuestionnaires were returned by 95 of 1383 members. Demographics comprised of 76% attendings with 94% practicing within an academic setting. Only 40% of radiologists reported that they knew most of the time whether a patient has received RT in the field scanned. A large majority of respondents (88%) felt that a history of prior radiation in a cancer patient was at least an occasional barrier that affected the ability to interpret imaging findings in a clinically useful way. The following types of information was considered helpful when interpreting a scan: screenshots of the radiation plan (85%), scrollable DICOM data on planning CT showing delivered RT dose lines (54%), and written text RT treatment summary (47%). Nearly all (89%) desired DICOM data within the clinical radiology Picture Archiving and Communication System system. Radiologists expected the ease of accessibility to RT plans to result in increased efficiency (76%) and accuracy (88%). ConclusionDiagnostic radiologists desire improved access and integration of radiotherapy plans into the diagnostic radiology clinical workup in the form of visual-spatial data.

Current and Emerging Roles of Whole-Body MRI in Evaluation of Pediatric Cancer Patients.

Imaging is fundamental to diagnosis and management of pediatric patients with cancer and cancer predisposition syndromes (CPSs). Whole-body MRI has emerged as a versatile tool for pediatric oncologic imaging, with the potential to spare children from ionizing radiation imparted by conventional modalities such as CT and PET. Whole-body MRI also enables simultaneous high-resolution local-regional staging and wide field-of-view distant staging in the same imaging session, with superior evaluation of the brain, spine, liver, and marrow. Recent technical advances have reduced imaging times and enhanced image quality, with continued advances on the near horizon. Pulse sequences such as whole-body diffusion-weighted imaging have also broadened the range of diagnostic information obtainable. In addition, increasing identification of children with CPSs has compelled efforts to establish surveillance imaging strategies for affected individuals, with whole-body MRI playing a pivotal role in screening algorithms for several CPSs. In light of these emerging trends, a working knowledge of oncologic whole-body MRI applications and evolving CPS surveillance algorithms is vital to providers who participate in the care of pediatric patients affected by or predisposed to cancer. Recognizing both the strengths and limitations of whole-body MRI not only enables more thoughtful implementation but also improves the accuracy of image interpretation. ©RSNA, 2019 See discussion on this article by Khanna .

Test of the RUSLE and Key Influencing Factors Using GIS and Probability Methods: A Case Study in Nanling National Nature Reserve, South China

The main purposes of the study were to test the performance of the Revised Universal Soil Loss Equation (RUSLE) and to understand the key factors responsible for generating soil erosion in the Nanling National Nature Reserve (NNNR), South China, where soil erosion has become a very serious ecological and environmental problem. By combining the RUSLE and geographic information system (GIS) data, we first produced a map of soil erosion risk at 30 m‐resolution pixel level with predicted factors. We then used consecutive Landsat 8 satellite images to obtain the spatial distribution of four types of soil erosion and carried out ground truth checking of the RUSLE. On this basis, we innovatively developed a probability model to explore the relationship between four types of soil erosion and the key influencing factors, identify high erosion area, and analyze the reason for the differences derived from the RUSLE. The results showed that the overall accuracy of image interpretation was acceptable, which could be used to represent the currently actual spatial distribution of soil erosion. Ground truth checking indicated some differences between the spatial distribution and class of soil erosion derived from the RUSLE and the actual situation. The performance of the RUSLE was unsatisfactory, producing differences and even some errors when used to estimate the ecological risks posed by soil erosion within the NNNR. We finally produced a probability table revealing the degree of influence of each factor on different types of soil erosion and quantitatively elucidated the reason for generating these differences. We suggested that soil erosion type and the key influencing factors should be identified prior to soil erosion risk assessment in a region.

Improvement of radiographer commenting accuracy of the appendicular skeleton following a short course in plain radiography image interpretation: A pilot study.

IntroductionRadiographers are at times required to provide preliminary information on plain radiography when significant findings are identified. The aim of the study was to evaluate the effectiveness of two short training modules to improve the accuracy of image interpretation of the appendicular skeleton amongst a group of radiographers.MethodsEight radiographers volunteered to participate in the study. All undertook a pre‐test and, following delivery of course materials, an immediate post‐test for two consecutive modules. A retention test was undertaken 6 months later. Sensitivity (Sn), specificity (Sp) and accuracy (Acc) scores were evaluated against the “Gold Standard” radiologists’ reports. Paired‐samples t‐tests were carried out to compare image interpretation scores between the start of module one to the end of module two, and between the end of module 2 and 6 months later. Summary receiver operating characteristics (SROC) scores on each of the participants’ module two post‐test study results were undertaken.ResultsSignificant improvements in scores were achieved between the mean (SD) scores of module 1 pre‐test (77.5 (±3.9)) and the module 2 post‐test (83.6 (±3.2) (P =0.022)). Sn, Sp and Acc scores increased from the start of module 1 pre‐test to the end of module 2 post‐test (Sn: 82.28–86.25%; Sp: 75.29–84.66%; Acc: 81.68–85.97%). The retention test revealed a non‐significant reduction in mean scores (80.0 (±5.1)) when compared to post‐test module 2 (83.6 (±3.2) (P =0.184)). SROC revealed an area under the curve of 0.90.ConclusionParticipants achieved significant improvements in commenting accuracy on plain radiography of the appendicular skeleton after completion of the two modules. However, continuous application and ongoing professional development is essential in order to maintain and develop the skills acquired.

THE CARRYING CAPACITY ON ECOSYSTEM SERVICES OF LAND USE CHANGE AT BORDER ENTIKONG

Entikong Region is located in Sanggau Regency, West Kalimantan Province, Indonesia, which is directly adjacent to Malaysia. Land use in the Border Area, which is massive and irregular, results in environmental degradation, deculturization, and lack of living standards of the community. High population growth in the border areas leads to excessive use of natural resources, and used land is not appropriately allocated. The land has limited function, and if the demand for the land is greater than the carrying capacity, there will be an imbalance that results in land degradation and its environment. The purpose of this study is to identify the type and extent of land function switch, analyze provider services as part of the Land Support Capacity Ecosystem services, and identify the Accuracy of Image Interpretation. The results showed that the increasing area of massive land use comes from a mixed plantation in 2017 increased by 60.6% of the total area of Entikong District. Degradation occurs in primary forest land use component which is only 18.6% of Entikong's total area in 2017. This indicates that the use of mixed plantation land acquires the protected forest, with many palm, rubber, and pepper. Similarly, the percentage of accuracy test from the interpretation result reaches 83.33% from 42 sample points in accordance with the real conditions. The Value of Clean Water Ecosystem Service Providers in 2011 was 0.36 and was 0.33 in 2017. Then within the period of almost 7 years, it is decreased by 0.03. Thus, the Ecosystem Service Index of clean water providers has a value less than 1, it means the function of the area as a provider of clean water is very small. Similarly, the Provider Ecosystem Services Index for Foodstuffs, the Value of Food Ecosystem Services Index in 2011 was 0.32 and was 0.31 in 2017, then within the nearly 7-year period, it is decreased by 0.01. The ecosystem services index as a food supply provider for the Entikong border area is very low (less than 1) which means the carrying capacity of the environment is not good enough for supplying food needs in Entikong. This indicates that there is a reduction in the availability of environmental services, and if it continues, then Environmental Assets declines sharply and services derived from nature will be lost or will be expensive in the near future. Thus, optimization and revitalization of land use are necessary by applying various policies related to development in the border area in Entikong District.&#x0D; Keywords: Borders, Land Use, Ecosystem Provider Services.&#x0D; &#x0D; References&#x0D; Admadhani, D. N., Hajil, A. H. S., &amp; Susanawati, L. D. (2013). Analysis of Water Supply and Water Demand for Carrying Capacity Assessment ( Case Study of Malang ). Journal of Natural Resources and Environment.&#x0D; Asdak, C., &amp; Salim, H. (2006). Water Resource Capacity As a Spatial Planning Consideration. Journal of Environmental Engineering P3TL-BPPT.&#x0D; Ernan Rustiadi, Sunsus Saefulhakim, D. R. P. (2011). Planning and Regional Development. Restpent Press.&#x0D; Ghozali. (2013). Referral of Land Use Utilization Through Ecological Footprint in Gresik Regency. Territory and Environment, 1 No.1, 67–78.&#x0D; Hamidy, Z. (2003). Land Cover Change, Composition, and Life Type in Suakaidupan Cikepuh. Faculty of Forestry, IPB.&#x0D; Muta’ali, L. (2015). Regional Analysis Techniques For Regional Planning, Spatial Planning, and Environment (Februari). Yogyakarta: Faculty of Geography UGM.&#x0D; National Standardization Department. (2010). Classification of Land Cover.&#x0D; Purwadhi. (2008). Introduction Remote Sensing Imagery Interpretation. Semarang: LAPAN.&#x0D; Riqqi, A. (2014). Design Concept Techniques Determination of Supporting Capacity and Capacity of the National Environment and Islands / Islands And Provinces. Bali: KLH.&#x0D; Saripin, I. (2003). Identify Land Use Using Landsat TM Imagery. Agricultural Engineering Bulletin.&#x0D; Varika. (2015). Monitoring of Ecosystem Service-Based Ecotourism (Recreation and Ecotourism) Capacity in 2000 and 2015 Using Landsat Image in Badung Regency, Bali.&#x0D; Viska. (2012). Land Use Direction in Batu City Based on Ecological Ecosystem Approach. Pomits Technique, 1 No.1, 1–6.&#x0D; &#x0D;

STUDY ON REMOTE SENSING IMAGE CHARACTERISTICS OF ECOLOGICAL LAND: CASE STUDY OF ORIGINAL ECOLOGICAL LAND IN THE YELLOW RIVER DELTA

Abstract. Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

Hybrid SPECT/CT Imaging in the Management of Differentiated Thyroid Carcinoma

Differentiated thyroid cancer (DTC) has a good prognosis overall; however, lifelong follow-up is required for many cases. Radioiodine planar imaging with iodine-123 (I-123) or radioiodine-131 (I-131) remains the standard in the follow-up after initial surgery and ablation of residual thyroid tissue using I-131 therapy. Radioiodine imaging is also used in risk-stratifying and for staging of thyroid cancer, and in long-term follow-up. Unfortunately, the lack of anatomical detail on planar gamma camera imaging and superimposition of areas presenting with increased radioiodine uptake can make accurate diagnosis and localization of radioiodine-avid metastatic disease challenging, leading to false positive results and potentially to over-treatment of patients. Hybrid SPECT/CT allows precise anatomical localization and superior characterization of foci of increased tracer uptake when compared to planar imaging. This, in turn, allows the differentiation of pathological and physiological uptake, increasing the accuracy of image interpretation and ultimately improving the accuracy of DTC staging and subsequent patient management. In this review, we look at the unique and emerging role that SPECT/CT plays in the management of DTC, illustrated by examples from our own clinical practice.

Sonographer-Identified Barriers and Facilitators to Prenatal Screening for Congenital Heart Disease

Background: Fetal ultrasound screening for congenital heart disease has high detection rates in efficacy studies but not in practice. We investigated sonographers’ perspectives on barriers to screening and their association with intermediate measures of cardiac imaging. Methods: Barriers to fetal heart screening were identified in focus groups with obstetric sonographers. A web-based survey measured reported barriers and sonographers’ ability to interpret fetal heart screening images. Generalized linear random effect models assessed associations between barriers and image interpretation. Results: Four themes were identified: intrinsic barriers (self-efficacy), external barriers (time), informational needs, and provider and patient expectations. Among 224 sonographers surveyed, an average of 77.6% of fetal heart images were interpreted correctly. Perceptions about self-efficacy ( P = .03) and ease of performing imaging ( P = .01) were associated with accuracy of image interpretation. Conclusions: Several sonographer-identified barriers associated with image interpretation may be novel targets for improving prenatal detection of congenital heart disease.

RadBench: Benchmarking image interpretation skills

PurposeThe key aim of this research was to develop an objective, accurate assessment tool with which to provide regular measurement and monitoring of image interpretation performance. The tool was a specially developed software program (RadBench) by which to objectively measure image interpretation performance en masse and identify development needs. MethodTwo test banks were generated (Test 1 & Test 2), each containing twenty appendicular musculoskeletal images, half were normal, half contained fractures. All images were double reported by radiologists and anonymised. A study (n = 42) was carried out within one calendar month to test the method and analysis approach. The participants included general radiographers (34), reporting radiographers (3), radiologists (2) (all from one UK NHS Trust) and medical imaging academics (3). ResultsThe RadBench software generated calculations of sensitivity, specificity, and accuracy in addition to a decision making map for each respondent. Early findings highlighted a 5% mean difference between image banks, confirming that benchmarking must be related to a specific test. The benchmarking option within the software enabled the user to compare their score with the highest, lowest and mean score of others who had taken the same test. Reporting radiographers and radiologists all scored 95% or above accuracy in both tests. The general radiographer population scored between 60 and 95%. ConclusionsThe evidence from this research indicates that the Radbench tool is capable of providing benchmark measures of image interpretation accuracy, with the potential for comparison across populations.

Diagnostic Value of MR Imaging in the Diagnosis of Adnexal Torsion.

To retrospectively evaluate the diagnostic performance of magnetic resonance (MR) imaging for the diagnosis of adnexal torsion in a series of patients with an equivocal adnexal mass at ultrasonography (US) in the context of acute or subacute pelvic pain. The institutional ethics committee approved the study and waived informed consent. All patients with acute or subacute pelvic pain who were undergoing MR examination for the exploration of an equivocal adnexal mass (January 2007 to December 2012) with surgical exploration or clinical and radiologic follow-up of at least 3 months were retrospectively included (n = 58). The prospective interpretations were recorded. Additionally, three radiologists who were blinded to the clinical, US, and surgical data retrospectively and independently reviewed MR images. Features associated with adnexal torsion were identified by using univariate and recursive partitioning multivariate analysis. Twenty-two patients (38%) had a diagnosis of adnexal torsion. The accuracy of MR imaging at the time of prospective interpretation was 80.6% (25 of 31 patients) and 85.1% (23 of 27 patients) in acute and subacute torsion, respectively. The accuracy of image interpretation by each retrospective reader was 83.9% (26 of 31 patients), 90.3% (28 of 31 patients), and 83.9% (26 of 31 patients) in the context of acute pelvic pain and 92.6% (25 of 27 patients), 88.9% (24 of 27 patients), and 81.5% (22 of 27 patients) in the context of subacute pelvic pain for readers 1, 2, and 3, respectively. At multivariate analysis, the whirlpool sign (odds ratio = 6.5 [95% confidence interval: 1.36, 31.0], P = .01) and a thickened tube (>10 mm) (odds ratio = 8.2 [95% confidence interval: 1.2, 56.8], P = .03) were associated with adnexal torsion, with substantial interreader agreement (κ = 0.71-0.84 and 0.82-0.86, respectively). The presence of adnexal hemorrhagic content was associated with nonviable ovaries in seven of 10 patients (70%) and with viable ovaries in 12 of 45 patients (27%) (P = .009). MR imaging is an accurate technique for the diagnosis of adnexal torsion in patients who have an adnexal mass with acute or subacute pelvic pain.