Objective Image Analysis Research Articles

Fast computation of inverse Meixner moments transform using Clenshaw’s formula

Orthogonal moments are recognized as useful tools for object representation and image analysis. It was shown that they have better image representation capability than the continuous orthogonal moments. One problem concerning the use of moments is the high computational cost, which may limit where the online computation is required. In this paper, we propose a recursive method based on Clenshaw’s recurrence formula that can be implemented to transform kernels of Meixner moments and its inverse for fast computation. There is no need for the proposed method to compute the Meixner polynomial values of various orders on various data points, where the computational complexity is reduced. Experimental results show that the proposed method performs better than the existing methods in term of computation speed and the effectiveness of image reconstruction capability in both noise-free and noisy conditions.

Simulation images of external objects in a virtual simulator for training human-machine systems operators

The article presents the results of a study of the contour analysis algorithm developed by the authors for automatic recognition of objects in an image with their subsequent modeling in virtual simulators for training human-computer systems operators. The main distinctive feature of the developed contour analysis algorithm is the use of image convolution in four directions and the tracing procedure, which makes it possible to more accurately search for the contour of objects compared to other algorithms of this type. The results of the study of the algorithm are given. Based on this study, recommendations on the choice of the parameters of the algorithm are given. As a result of the analysis of three-dimensional modeling methods, it was concluded that for the effective implementation of three-dimensional graphics in virtual simulators for training human-machine system operators, it is advisable to use an algorithm for contour image analysis of external objects.

Multi Spectral Satellite Data to Investigate Land Expansion and Related Micro Climate Change as Threats to the Environment

Technology development of satellite earth observation offers multi-spectral data, variations sensitivity of satellite sensors are very useful to detect existing conditions by using the remote sensing algorithm to extract the land cover and the phenomenon that has occurred. Ecosystems have bound tolerance to nature condition and organisms have adaptation limit to climate change. Method used in this study was the extraction of land cover by applying multi spectral analysis as Maximum Likelihood, object base image analysis, (LST) land surface temperature, and also the formula Threat of Land Expansion (TLE) to the environment. Result showed that multispectral and time series analysis gave the increasing dynamic of land expansion, especially for forest high density, which areas ranged from 29098.73 ha in 2000 to 19216.7 ha in 2018. The surface temperature increase was ± 2.8 C° in eighteen years. The temperature dynamic represented the micro climate changes, has followed stream of land expansion. TLE represented zone threats of land expansion to natural ecosystems. It was found that threat zone because land expansion. The area of high threat vale 0.4 around central human activity was a built up area.

C.03 Deformation-based morphometry analysis of longitudinal low-grade glioma growth

Background: Diffuse low-grade gliomas (LGGs) are primary brain tumours with infiltrative, anisotropic growth related to surrounding white and grey matter structures. Deformation-based morphometry (DBM) is a simple and objective image analysis method that can identify areas of local volume change over time. In this study, we illustrate the use of DBM to study the local expansion patterns of LGGs monitored by serial magnetic resonance imaging (MRI). Methods: We developed an image processing pipeline optimized for the study of LGG growth involving the fusion of follow-up MRIs for a given patient into an average template space using nonlinear registration. The displacement maps derived from nonlinear registration were converted to Jacobian maps, which estimate local tissue expansion and contraction over time. Results: Our results demonstrate that neoplastic growth occurs primarily around the edges of the tumour while the lesion core and areas adjacent to obstacles, such as the skull, show no significant expansion. Regions of normal brain tissue surrounding the lesion show slight contraction over time, representing compression due to mass effect of the tumour. Conclusions: DBM is a useful tool to understand the long-term clinical course of individual tumours and identify areas of rapid growth, which may explain the current presentation and/or predict future symptoms.

Texture analysis of myocardial infarction in CT: Comparison with visual analysis and impact of iterative reconstruction

ObjectivesTo compare texture analysis (TA) with subjective visual diagnosis of myocardial infarction (MI) in cardiac computed tomography (CT) and to evaluate the impact of iterative reconstruction (IR). MethodsTen patients (4 women, mean age 68 ± 11 years) with confirmed chronic MI and 20 controls (8 women, mean age 52 ± 11 years) with no cardiac abnormality underwent contrast-enhanced cardiac CT with the same protocol. Images were reconstructed with filtered back projection (FBP) and with advanced modeled IR at strength levels 3–5. Subjective diagnosis of MI was made by three independent, blinded readers with different experience levels. Classification of MI was performed using machine learning–based decision tree models for the entire data set and after splitting into training and test data to avoid overfitting. ResultsSubjective visual analysis for diagnosis of MI showed excellent intrareader (kappa: 0.93) but poor interreader agreement (kappa: 0.3), with variable performance at different image reconstructions. TA showed high performance for all image reconstructions (correct classifications: 94%–97%, areas under the curve: 0.94–0.99). After splitting into training and test data, overall lower performances were observed, with best results for IR at level 5 (correct classifications: 73%, area under the curve: 0.65). ConclusionsAs compared with subjective, nonreliable visual analysis of inexperienced readers, TA enables objective and reproducible diagnosis of chronic MI in cardiac CT with higher accuracy. IR has a considerable impact on both subjective and objective image analysis.

Pelvis imaging: Achieving dose reduction with different patient positions

The purpose of this research was to determine how dose area product, effective dose, absorbed doses to specific organs, and image quality changed according to different automatic exposure control positions in pelvis imaging. The research was carried out in two parts. The study was conducted on an anthropomorphic phantom and 200 patients referred to pelvic imaging. We measured the dose area product, field size, height, and mass. Then we calculated the effective dose and absorbed dose for individual organs accordingly. Lateral ionizing cells were first positioned in line with the iliac crests (head towards position) and subsequently, with the femoral neck (head away position). All the images were independently evaluated by three radiologists using ViewDEX and objective image analysis was performed measuring contrast-to-noise ratio and signal-to-noise ratio. We found no significant differences in the Siemens Luminos unit in any of the inspected parameters. However, there was a significant difference in dose area product (37.3 %), effective dose (35.7 %) and average absorbed dose to selected individual organs (36.7 %) when the head away position of the patient was used and the image quality increased. Based on these results, we can propose that the optimal position of the patient regarding the ionizing cells is the head away position.

Rotational Stability and Centration of a New Toric Lens Design Platform Using Objective Image Analysis Over 6 Months.

To determine the rotational stability of the Rayner 600S intraocular lens (IOL) (Rayner, Worthing, United Kingdom) using objective image analysis techniques. A total of 66 patients (mean age: 69.92 ± 8.45 years) with healthy eyes presenting for routine cataract surgery were implanted monocularly with the 600S IOL and followed up over 90 to 180 days postoperatively. Images of the IOL were captured through a maximally dilated pupil (tropicamide 1.0%, phenylephrine 2.5%) immediately after surgery and after 1 to 3 days, 30 days, and 90 to 180 days using a digital slit-lamp biomicro-scope. The orientation of the IOL markings were image analyzed compared to conjunctival blood vessel landmarks visible across all time points to correct for head and rotation. Centration was assessed by drawing ovals to circumscribe the IOL, pupil, and limbus to compare the centers (0.01 mm per-pixel resolution). Absolute values for rotation postoperatively were 1.60° ± 1.13° at 1 to 3 days, 1.58° ± 1.36° at 30 days, and 1.83° ± 1.44° at 90 to 180 days. No lens rotated more than 5°. The average centration relative to the limbus was -0.04 ± 0.25 mm horizontally and 0.04 ± 0.26 mm vertically at 1 to 3 days, 0.00 ± 0.38 mm vertically and 0.01 ± 0.28 mm horizontally at 30 days, and 0.08 ± 0.37 mm vertically and 0.07 ± 0.47 mm horizontally at 90 to 180 days. The Rayner 600S IOL showed exceptional rotational stability and centration after implantation, meeting the U.S. Food and Drug Administration prescribed American National Standards Institute standards for toric IOLs. [J Refract Surg. 2019;35(1):48-53.].

Objective image analysis of non-magnifying image-enhanced endoscopy for diagnosis of small depressed early gastric cancers.

Background Gastric cancers (GC) after H. pylori eradication are difficult to diagnose even by magnifying narrow-band imaging (NBI) or blue laser imaging (BLI) endoscopy. Little is known with regard to non-magnifying (NM)-NBI/BLI for early GC so we examined the efficacy of NM-NBI/BLI for early GC diagnosis. Methods We retrospectively analyzed the images of 29 small (≤ 1 cm) intramucosal GC that had been treated with endoscopic submucosal dissection and 137 benign depressed lesions (BDLs). The brightness and shape of the GCs and BDLs by NM-NBI/BLI were assessed with ImageJ software. Results The NBI/BLI-index, which indicates the brightness of NBI/BLI for visualization, was significantly higher in GC than BDLs in both the H. pylori -infected ( P = 0.009) and -eradicated group ( P < 0.0001), indicating that GC exhibited brighter colors than the normal surrounding mucosa. The C-index, which refers to the circularity of the lesion, was also significantly higher in GC than BDLs in both H. pylori -infected ( P = 0.006) and -eradicated cases ( P = 0.004). Based on receiver-operating characteristic curve analysis, cutoff values for the NBI/BLI- and C-indices for GC were 1.04 and 0.58 in the H. pylori -infected cases, and 0.98 and 0.64 in the H. pylori -eradicated cases. With the reference value of the NBI/BLI-index set at ≥ 0.69 with the C-index at ≥ 0.21 in the H. pylori -infected and the NBI/BLI-index at ≥ 0.80 with the C-index at ≥ 0.32 in the H. pylori -eradicated cases, both the sensitivity and negative predictive value for early GC were 100 %. A high NBI/BLI-index tended to be associated with a wide length of the intervening part histologically in the H. pylori -eradicated cases ( P = 0.09). Conclusions The small depressed-type early GC had brighter color and rounder shape compared to BDLs in both H. pylori -infected and -eradicated cases. The NBI/BLI- and C-indices calculated by the image analysis may facilitate identification of small depressed-type GC.

Quality assurance guidance for scoring and reporting for pathologists and laboratories undertaking clinical trial work.

While pathologists have always played a pivotal role in clinical trials ensuring accurate diagnosis and staging, pathology data from prognostic and predictive tests are increasingly being used to enrol, stratify and randomise patients to experimental treatments. The use of pathological parameters as primary and secondary outcome measures, either as standalone classifiers or in combination with clinical data, is also becoming more common. Moreover, reporting of estimates of residual disease, termed ‘pathological complete response’, have been incorporated into neoadjuvant clinical trials. Pathologists have the expertise to deliver this essential information and they also understand the requirements and limitations of laboratory testing. Quality assurance of pathology‐derived data builds confidence around trial‐specific findings and is necessarily focused on the reproducibility of pathological data, including ‘estimates of uncertainty of measurement’, emphasising the importance of pathologist education, training, calibration and demonstration of satisfactory inter‐observer agreement. There are also opportunities to validate objective image analysis tools alongside conventional histological assessments. The ever‐expanding portfolio of clinical trials will demand more pathologist engagement to deliver the reliable evidence‐base required for new treatments. We provide guidance for quality assurance of pathology scoring and reporting in clinical trials.

Impact of Single-Energy Metal Artifact Reduction on CT image quality in patients with dental hardware

BackgroundTo evaluate whether Canon's Single-Energy Metal Artifact Reduction (SEMAR) algorithm can significantly improve subjective and objective image quality of patients with nonremovable dental hardware undergoing CT imaging of the oral cavity and oropharynx. Materials and methodsSEMAR was reconstructed from routine Adaptive Iterative Dose Reduction (AIDR) images in 154 patients (46 females and 108 males; mean age 66.3 ± 10.5 years). Subjective SEMAR and AIDR image quality of the mouth floor, sublingual glands, lymphatic ring and overall impression were evaluated by two independent radiologists on a 6-point scale (1 = very good image quality, 6 = poor image quality) and compared to ratings of an oral and maxillofacial surgeon. Interrater agreement was assessed using the intraclass correlation coefficient (ICC). Objective image analysis was performed by placing regions of interest (ROIs) on the mouth floor and measuring CT attenuation in Hounsfield units (HU) and standard deviation (SD). ResultsSEMAR significantly improved subjective image quality in all evaluated structures for all raters (p < 0.001). Furthermore, SEMAR significantly reduced objective metal artifacts and image noise (p < 0.001). ConclusionSEMAR significantly improved diagnostic quality of CT images of the oral cavity and oropharynx by reducing artifacts caused by dental hardware.

Spatial arrangement of stainless steel fibers within hybrid yarns designed for electromagnetic shielding

Yarns containing textile fibers and fine metal fibers in their structure are often used to produce electrically conductive fabrics. The blending quality of the fiber components in a yarn significantly affects the properties of the yarn and the produced fabric. Therefore, the arrangement of metal fibers in yarn structures needs to be analyzed, which can be done using image analysis and spatial statistics methods. One of the aims of this paper is to introduce a suitable methodology for obtaining adequate cross-sections of a yarn containing metal fibers that would allow the usage of objective image analysis methods to identify the component fibers for subsequent evaluation of spatial arrangement. In this paper, an algorithm for the objective segmentation of the component fibers in a yarn cross-section is proposed, and a methodology for evaluating the spatial arrangement of fibers using spatial statistics data is presented. The second aim is to study the specific arrangement of the fibers in hybrid yarns containing 20 wt% of a conductive component, more precisely extremely thin discrete stainless steel fibers, by the proposed methodology. Based on the results, it is concluded that the metal fibers in the cross-sections of this hybrid yarn are randomly arranged.

Tradeoff between noise reduction and inartificial visualization in a model-based iterative reconstruction algorithm on coronary computed tomography angiography.

We aimed to evaluate the image quality performance of coronary CT angiography (CTA) under the different settings of forward-projected model-based iterative reconstruction solutions (FIRST).Thirty patients undergoing coronary CTA were included. Each image was reconstructed using filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR-3D), and 2 model-based iterative reconstructions including FIRST-body and FIRST-cardiac sharp (CS). CT number and noise were measured in the coronary vessels and plaque. Subjective image-quality scores were obtained for noise and structure visibility.In the objective image analysis, FIRST-body produced the significantly highest contrast-to-noise ratio. Regarding subjective image quality, FIRST-CS had the highest score for structure visibility, although the image noise score was inferior to that of FIRST-body.In conclusion, FIRST provides significant improvements in objective and subjective image quality compared with FBP and AIDR-3D. FIRST-body effectively reduces image noise, but the structure visibility with FIRST-CS was superior to FIRST-body.

An objective image analysis method for estimation of canopy attributes from digital cover photography

A method was proposed to remove the subjectivity of gap size analyses approaches implemented by default in cover photography. The method yielded robust and replicable measurements of forest canopy attributes. Digital cover photography (DCP) is an increasingly popular method to estimate canopy attributes of forest canopies. Compared with other canopy photographic methods, DCP is fast, simple, and less sensitive to image acquisition and processing. However, the image processing steps used by default in DCP have a large substantial subjective component, particularly regarding the separation of canopy gaps into large gaps and small gaps. In this study, we proposed an objective procedure to analyse DCP based on the statistical distribution of gaps occurring in any image. The new method was tested in 11 deciduous forest stands in central Italy, with different tree composition, stand density, and structure, which is representative of the natural variation of these forest types. Results indicated that the new method removed the subjectivity of manual and semi-automated gap size classifications performed so far in cover photography. A comparison with direct LAI measurements demonstrated that the new method outperformed the previous approaches and increased the precision of LAI estimates. Results have important implications in forestry, because the simplicity of the method allowed objective, reliable, and highly reproducible estimates of canopy attributes, which are largely suitable in forest monitoring, where measures are routinely repeated. In addition, the use of a restricted field of view enables implementation of this photographic method in many devices, including smartphones, downward-looking cameras, and unmanned aerial vehicles.

Whole-body ultra-low dose CT using spectral shaping for detection of osteolytic lesion in multiple myeloma.

The aim of this study was to investigate the radiation dose and image quality of a whole-body low-dose CT (WBLDCT) using spectral shaping at 100 kV (Sn 100 kV) for the assessment of osteolytic lesions in patients with multiple myeloma. Thirty consecutive patients were retrospectively selected, who underwent a WBLDCT on a third-generation dual-source CT (DSCT) (Sn 100 kV, ref. mAs: 130). They were matched with patients, who were examined on a second-generation DSCT with a standard low-dose protocol (100 kV, ref. mAs: 111). Objective and subjective image quality, radiation exposure as well as the frequency of osteolytic lesions were evaluated. All scans were of diagnostic image quality. Subjective overall image quality was significantly higher in the study group (p = 0.0003). Objective image analysis revealed that signal intensities, signal-to-noise ratio and contrast-to-noise ratio of the bony structures were equal or significantly higher in the control group. There was no significant difference in the frequency of osteolytic lesions (p = 0.259). The median effective dose of the study protocol was significantly lower (1.45 mSv vs. 5.65 mSv; p < 0.0001). WBLDCT with Sn 100 kV can obtain sufficient image quality for the depiction of osteolytic lesions while reducing the radiation dose by approximately 74%. • Spectral shaping using tin filtration is beneficial for whole-body low-dose CT • Sn 100 kV yields sufficient image quality for depiction of osteolytic lesions • Whole-body low-dose CT can be performed with a median dose of 1.5 mSv.

Contribution of color to material perception

Color vision enables us to discriminate objects based on the wavelength composition of reflected light, but this is not all about the functional contributions of color to visual recognition. Since a trichromatic image carries more information about the optical properties of a scene than a monochromatic image does, color could help us recognize complex material qualities. For instance, color vision assists our gloss perception. For glossy dielectric materials, the spectral distribution of illumination is preserved in the specular reflection, while modulated by surface light absorption for the diffuse reflection. When this physical constraint holds (e.g., red highlights on red body, white highlights on red body), human observers perceive naturalistic glossy surfaces. However, when the constraint is violated (e.g., red highlights on white body, red highlights on green body), the highlights look unnatural (Nishida et al., VSS 2008, 2011). We also found that human vision uses color statistics of an image for the perception of an ecologically important surface condition, i.e., wetness (Sawayama, Adelson & Nishida, 2017, Journal of Vision). Psychophysical experiments showed that overall enhancement of chromatic saturation, combined with a luminance tone change that increases the darkness and glossiness of the image, tends to effectively make dry scenes look wetter. Theoretical analysis along with image analysis of real objects indicated that our image transformation, which we call the wetness enhancing transformation (WET), is consistent with actual optical changes produced by surface wetting.

Retrieval of crosswind velocity based on the analysis of remote object images: Part 2—Drift of turbulent volume

Possibilities for the crosswind profiling along a path of observation of a distant object from the analysis of the video sequence of its images are studied in this work by numerical simulation. The method suggested for wind velocity estimation is based on the analysis of two adjacent incoherent images and exhibits better performance in comparison with counterparts, which is explained by there being no need to accumulate statistics of the parameters analyzed. A new method for the filtration of turbulent distortions of an image by their characteristic sizes is suggested with the aim of estimating the wind velocity in different segments of an observation path. The work shows a possibility of determining the drift velocity of several (no less than three) layers of turbulent atmosphere, located at different positions between the object observed and receiving optical system, under certain turbulent conditions.

Influence of Artifact Reduction Tools in Micro–computed Tomography Images for Endodontic Research

IntroductionMicro–computed tomography (μCT) is an imaging modality of growing application in endodontic research because of its nondestructive technology that enables visualization at the micrometer level. In the presence of high-density material, images acquired with μCT may present artifacts. Thus, the aim of this study was to evaluate subjectively and objectively the influence of artifact reduction tools available for μCT image reconstruction to determine whether their use can influence endodontic research outcomes. MethodsTen teeth were scanned in a μCT device, and these images were reconstructed by applying 13 protocols of artifact reduction tools, combining ring artifact reduction (RAR) and beam-hardening artifact reduction (BAR). Images were assessed subjectively (observer's preference) and objectively (root canal surface area and volume). Observer's preference for RAR and BAR protocols was tested by χ2. Analysis of variance was used to compare volumes and surface area of root canals on different protocols. Intraobserver and interobserver reproducibility was calculated by the weighted kappa test. ResultsThere was no preference for a particular protocol for BAR (P = .91) or RAR (P = .80). There were no statistically significant differences for volume (P = .999) or surface area (P = .972) of root canals for all protocols. ConclusionsTo evaluate root canal volume and root canal surface area, artifact reduction tools applied to μCT images can be used according to the observer's visual preference without influence on objective image analysis.

Assessment of age- and sex-related changes in baggy lower eyelids using a novel objective image analysis method: Orbital gray scale analysis.

Baggy lower eyelids (BLEs) are a common aesthetic problem of aging. Valid and reliable assessment tools for BLEs are required to evaluate the current status and treatment outcome. Age- and sex-related changes in BLEs were assessed with the orbital gray scale (OGS), a novel objective image analysis method. We gathered frontal-view photographs of the faces of the patients who sought for correction of BLEs. Based on the clinical pattern, we classified the BLEs of the subjects into medial (M), medial and central (MC), and medial to lateral (MCL) types. Severity was evaluated using the OGS, a modified method of the linear gray scale analysis. The BLEs of 1034 subjects were classified. The most common types were MCL type in the men and MC type in the women, respectively. The M and MC types were common in the young subjects, whereas the MCL type was more common in the old subjects (P<.001). The measurements of OGS in 104 subjects showed positive correlation with age, a higher mean value in the men, and a trend toward higher values in the order of M, MC, and MCL types (P<.001 for central and lateral OGS scores). In a multiple linear regression analysis, central and lateral OGS values were significantly related with age, sex, and M-C-L classification type (P<.001). The M-C-L classification and OGS were significantly associated with both age and sex, proving that they could be potent objective assessment tools for BLEs.

Retrieval of crosswind velocity based on the analysis of remote object images: Part 1 — drift of a thin layer of turbulent inhomogeneities

Numerical simulation is carried out in order to estimate possibilities of crosswind velocity determination along an observation path between a distant object and observer. The estimation is based on the analysis of atmospheric distortions in the object images. The disturbing effect of limited atmospheric regions on the object image and possibilities of the drift velocity retrieval in these regions are analyzed. A new method for filtration of turbulent distortions by their characteristic sizes is suggested with the aim of estimating the wind velocity at different segments of the observation path. It is shown that the technique suggested allows one to determine crosswind velocity with high accuracy when it is applied to a thin layer of atmospheric inhomogeneities.

Visual wetness perception based on image color statistics

Color vision provides humans and animals with the abilities to discriminate colors based on the wavelength composition of light and to determine the location and identity of objects of interest in cluttered scenes (e.g., ripe fruit among foliage). However, we argue that color vision can inform us about much more than color alone. Since a trichromatic image carries more information about the optical properties of a scene than a monochromatic image does, color can help us recognize complex material qualities. Here we show that human vision uses color statistics of an image for the perception of an ecologically important surface condition (i.e., wetness). Psychophysical experiments showed that overall enhancement of chromatic saturation, combined with a luminance tone change that increases the darkness and glossiness of the image, tended to make dry scenes look wetter. Theoretical analysis along with image analysis of real objects indicated that our image transformation, which we call the wetness enhancing transformation, is consistent with actual optical changes produced by surface wetting. Furthermore, we found that the wetness enhancing transformation operator was more effective for the images with many colors (large hue entropy) than for those with few colors (small hue entropy). The hue entropy may be used to separate surface wetness from other surface states having similar optical properties. While surface wetness and surface color might seem to be independent, there are higher order color statistics that can influence wetness judgments, in accord with the ecological statistics. The present findings indicate that the visual system uses color image statistics in an elegant way to help estimate the complex physical status of a scene.