Computed Tomography Research Articles

CBCT Guidance for Removing Foreign Object from the Jawbone: A Case Study

AbstractForeign objects lodged in the mandibular bone often result from trauma or dental procedures. Accurate localization of these foreign objects is crucial for guided surgical removal, especially when patients present with persistent pain. Conventional imaging modalities like periapical and panoramic radiographs may not provide sufficient detail for precise localization. Cone beam computed tomography (CBCT) has emerged as a valuable tool for guided surgical interventions owing to its superior imaging capabilities. We present two cases of foreign objects lodged in the mandible, where patients complained of prolonged pain, soreness, and numbness in the right mandible extending to the head and behind the ear. Both patients had undergone previous right mandibular tooth extractions and received treatment from a neurologist without resolution of symptoms. Both cases showed the control improvement in complaints, and no paresthesia or postoperative complications were found. CBCT-guided surgical removal was performed in both cases, revealing a metal specimen measuring 6 × 3 × 1 mm3 in the first patient and a remaining root measuring 5 × 3 × 2 mm3 in the second patient. Diagnosing foreign objects in the mandible poses challenges due to their varied size, composition, and proximity to vital structures. CBCT offers superior imaging resolution, enabling precise localization and assessment of anatomical relationships, such as the distance to the inferior alveolar nerve and surrounding boundaries. CBCT emerges as the preferred imaging modality for diagnosing and guiding the surgical removal of foreign objects in the mandible. Its advantages include accurate localization, low radiation exposure, and cost-effectiveness. Compared with CT scans, CBCT also offers faster scanning times, making it a valuable tool in clinical practice for managing such cases

3D imaging techniques for the diagnosis and surgical planning of complex limb fractures: a systematic review

This systematic study will investigate how 3D imaging techniques have improved diagnosis and planning of surgeries for complex limb fractures. These fractures are caused of high-energy trauma which presents unique challenges, so advanced imaging technologies can help to mitigate them. We strictly adhere PRISMA guidelines to ensure thorough analysis and inclusion of relevant literature. The search was conducted on Web of Science and PubMed were all thoroughly searched between 2010 and 2023. Keyword combinations such as "3D imaging," "complex limb fractures," and "surgical planning" were employed using Boolean operators and as a result, 26 studies were included following screening based on strict inclusion criteria. 56% of studies used CT scans, demonstrating a 32% increase in diagnosis accuracy over 2D techniques for complicated fractures. In 28% of cases MRI improved soft tissue evaluation. 3D printing was utilized in 16% of investigations and it improved postoperative alignment in 94% of cases and shortened operating times by 18%. We can conclude that 3D imaging greatly enhances surgical planning, patient outcomes, and diagnostic precision in complex limb fractures and it provides useful resources for surgeons and patients by improving fracture visualization, reducing operating time, and promoting quicker recovery.

Primary clear cell adenocarcinoma of the seminal vesicle with ovarian homology: A rare case report

Rationale: Primary seminal vesicle adenocarcinoma is a rare type of male reproductive system tumor, primarily manifesting as papillary adenocarcinoma. Meanwhile, clear cell adenocarcinoma (CCA) is a common malignancy in the female reproductive system. Therefore, the occurrence of CCA in the seminal vesicle, showing ovarian homology, is even rarer. This pathological type of seminal vesicle cancer has been seldom reported. Patient concerns: A 43-year-old male patient presented to the outpatient clinic with a decade-long history of intermittent hemospermia accompanied by a 2-month sensation of dragging in the left lower abdomen. Following an MRI scan that indicated a seminal vesicle mass, he was admitted for further treatment. Diagnosis: The MRI revealed 2 abnormal signal mass lesions located between the left side of the pelvic cavity, the prostate, and the left seminal vesicle, primarily exhibiting long T1 and long T2 cystic characteristics. The CT scan with enhancement showed mixed density mass shadows in the left seminal vesicle area of the pelvic cavity, with mild arterial phase enhancement and continued enhancement in the portal phase. Physical examination revealed mild tenderness in the lower left abdomen. Digital rectal examination detected a hard mass above the left prostate, with no bloodstain on the glove, and no other significant abnormalities were observed. Routine urinalysis and biochemistry did not reveal any notable abnormalities. Tumor markers were all within normal ranges. Interventions: The tumor was completely excised laparoscopically and sent for pathological examination. Nine days postoperatively, the patient was successfully discharged. Outcomes: Postoperative pathology indicated primary CCA of the seminal vesicle. During a 20-month follow-up via telephone, the patient reported a generally good condition without significant discomfort. Lessons: CCA occurring in the seminal vesicle is extremely rare, and radical surgical excision is the primary treatment method.

Eagles’ syndrome: is it the longest styloid process length to date? A case report and an overview of the literature

Eagle syndrome is a rare condition that occurs when the styloid process, a bony projection in the skull, becomes elongated and causes pain in the head, neck, and face. The causes of Eagle syndrome are not entirely clear, but it is believed to be related to a genetic predisposition or trauma to the head or neck. The most common symptoms of Eagle syndrome include a sharp pain in the throat or ear, difficulty swallowing, and a feeling of a foreign object in the throat. Other symptoms may include headaches, facial pain, and neck pain. Diagnosis of Eagle syndrome can be challenging as symptoms can be mistaken for other conditions such as myofascial pain syndromes, glossopharyngeal or trigeminal neuralgias, migraine and cervical arthritis. However, proper diagnosis can be established by performing adequate physical examination, taking clear medical history, and full workup including imaging tests such as X-rays, CT scans, or MRIs to confirm the diagnosis.

V–V ECMO for severe Chlamydia psittaci pneumonia presenting with sudden cardiac arrest: A case report and literature review

Rationale: Psittacosis, also known as parrot fever, is an infectious disease caused by Chlamydia psittaci, which can lead to C psittaci pneumonia. Clinical manifestations are highly nonspecific, which can vary from asymptomatic infection to severe pneumonia and even death. Patient concerns: In this case presentation, we reported one 65-year-old male case of C psittaci pneumonia who was admitted to our hospital on December 2, 2022 due to the chief complaints of poor appetite and fatigue for 3 days as the clinical manifestations. He denied contact with birds but admitted riding horses 1 week ago. Diagnoses: Chlamydia psittaci pneumonia of patient was confirmed through metagenomic sequencing of bronchoalveolar lavage fluid under bronchoscopy. Intervention: Patient was treated with V-V ECMO, invasive mechanical ventilation and CRRT. Outcomes: On December 12, the patient was successfully weaned off V–V ECMO and discharged on December 20, 2022. During postoperative follow-up, CT scan in a local hospital revealed the infiltrative lesions of the lung were absent. Lessons: This case prompts that metagenomic next-generation sequencing is a feasible diagnostic tool for psittacosis, which can rapidly worsen and even cause sudden cardiac arrest. V–V ECMO might be a viable emergency therapeutic option.

Nasal and temporal intraconal orbital fat densities differ on computerized tomographic scans of normal orbits

AbstractBackground and AimThe anatomy and function of different areas within the intraconal fat remain poorly understood. A potential difference between nasal and temporal orbital fat densities in normal eyes may assist clinicians and radiologists in more accurately interpreting computerized tomographic (CT) scans and making more informed diagnostic and therapeutic decisions for patients with orbital pathologies.Patients and MethodsData from randomly selected patients who underwent orbital CT scans at Sheba Medical Center in 2022 were analyzed. Patients with abnormal imaging findings in either orbit were excluded. Intraconal orbital fat density was measured in six nasal and temporal sites by means of Hounsfield units (HU).ResultsThe study included 54 patients (mean age 45.3 ± 25.5 years, 29 [54%] females) who were scanned for ophthalmologic etiologies unrelated to the orbit. Non-contrast-enhanced (NCE)-CT scans were available for 36 patients (67%), CE-CT scans for 31 patients (57%), and both CE and NCE scans for 13 patients. HU values were significantly higher in the nasal orbit compared to the temporal orbit on both NCE-CT (−75.8 ± 7.5 nasal vs. −78.1 ± 8.4 temporal, P < 0.001) and CE-CT (−72.7 ± 6.7 nasal vs. −74.6 ± 8.6 temporal, P = 0.02). Age, sex, and laterality had no effect on the HU values.ConclusionsThe density of nasal intraconal fat is higher compared to temporal intraconal fat, as observed on both CE and NCE-CT scans of normal eyes.These results suggest the presence of anatomical differences between these compartments and could have significant clinical implications in the diagnosis of various orbital pathologies.

COVID-19 CT Image Segmentation Based on Modified U-Net

Abstract. This paper presents a COVID-19 CT image segmentation method based on a modified U-Net model. In the study and treatment of COVID-19, the segmentation of CT images is crucial for understanding the virus's impact on lung tissues. Traditional image segmentation methods have limitations when dealing with the complex lung lesions caused by COVID-19. Therefore, we optimized the U-Net model's structure and introduced an efficient loss function along with image enhancement techniques to improve segmentation accuracy and computational efficiency. Experiments were conducted on the Medseg and Radiopaedia datasets. The results demonstrate that the modified U-Net model outperforms traditional methods in terms of segmentation accuracy and computational efficiency. Additionally, we discuss the advantages and limitations of the model and propose directions for future research.

Machine Learning Models Based on [18F]FDG PET Radiomics for Bone Marrow Assessment in Non-Hodgkin Lymphoma

Non-Hodgkin lymphoma is a heterogeneous group of cancers that triggers bone marrow infiltration in 20–40% of cases. Bone marrow biopsy in combination with a visual assessment of [18F]FDG PET/CT images is used to assess the marrow status. Despite the potential of both techniques, they still have limitations due to the subjectivity of visual assessment. The present study aims to develop models based on bone marrow uptake in [18F]FDG PET/CT images at the time of diagnosis to differentiate bone marrow status. For this purpose, a model trained for skeleton segmentation and based on the U-Net architecture is retrained for bone marrow segmentation from CT images. The mask obtained from this segmentation together with the [18F]FDG PET image is used to extract radiomics features with which 11 machine learning models for marrow status differentiation are trained. The segmentation model yields very satisfactory results with Jaccard and Dice index values of 0.933 and 0.964, respectively. As for the classification models, a maximum F1_score_weighted and F1_score_macro of 0.962 and 0.747, respectively, are achieved. This highlights the potential of these features for bone marrow assessment, laying the foundation for a new clinical decision support system.

Peripheral Ameloblastoma: A Case Report and Review of Literature

Peripheral ameloblastoma (PA) is a rare benign tumor that can occur mostly in the mandibular gingiva of the premolar area, originating from the residual odontogenic epithelium. The patient is usually asymptomatic and the lesion can be an occasional finding during routine intraoral examination. Due to the lack of clinical and radiographic pathognomonic features, the diagnosis is based on histopathological analysis, associated with 3D computed tomography (CT) imaging. Here, we report the case of a middle-aged man showing an asymptomatic, sessile, normochromic papillomatous mass of the lingual alveolar mucosa, in correspondence of tooth 4.4, which was histologically diagnosed as peripheral ameloblastoma. After the complete excision of the lesion, there were no recurrence and no symptoms during the 3-year follow-up. The treatment of choice for PA is a conservative surgical excision, which usually results in a good prognosis, together with a long-term follow-up, necessary to intercept possible recurrence or, more rarely, malignant transformation.

Three-Dimensional Micromechanical Simulation and Evaluation of High-Toughness Ultra-Thin Friction Course with X-Ray Computed Tomography

As a novel pavement wear layer material, the micromechanical mechanisms of High-toughness Ultra-thin Friction Course (HUFC) have not been fully elucidated. This paper presents a new method for the three-dimensional micromechanical simulation of high-toughness asphalt mixtures based on a viscoelastic parameter calibration model. X-ray Computerized Tomography (CT) was employed to scan samples of high-toughness asphalt mixtures to obtain detailed information on the internal structure (aggregate, fine aggregate matrix FAM and voids), and a three-dimensional micromechanical model was constructed based on the real-scale distribution of these components. Aggregates in the high-toughness asphalt mixture were modeled as elastic bodies, while FAM was treated as a viscoelastic material characterized by the Burgers model. Using the Boltzmann linear superposition principle and Laplace transform theory, the viscoelastic properties of FAM were converted into Prony parameters recognizable by finite element software, and the viscoelastic parameters were calibrated. Micromechanical simulations were conducted for three different gradings of high-toughness asphalt mixtures, and the results show that the predicted deformation closely matched the measured deformation. This method accurately reflects the deformation characteristics of different gradings of high-toughness asphalt mixtures, overcoming the limitations of traditional numerical simulations based on homogeneous material models. It represents an advancement and refinement of micromechanical simulation methods for high-toughness asphalt mixtures.

Speech Perception Outcomes with the Anatomy-Based Fitting Map Among Experienced, Adult Cochlear Implant Users: A Longitudinal Study.

Introduction: Anatomy-based fitting (ABF), a relatively new technique for cochlear implant programming, attempts to lessen the impact of the electrode insertion location-related frequency-to-place mismatch (FPM). This study aimed to compare vowels and consonant perception in quiet and in noise among experienced adult cochlear implant (CI) users using the ABF and the regular, conventional-based fitting (CBF) map (pre-ABF) over six months. Method: Nine ears from eight experienced adult CI users were included in the experimental and longitudinal research. Using surgical planning software called Otoplan, post-operative computed CT scans were used to determine the locations of intracochlear electrodes and their angle of insertion. The anatomy-based frequency bands were produced by Maestro 9.0 CI fitting software using the Otoplan data. Nonsense syllables with consonant-vowel-consonant (CVC) recognition scores in quiet and noise (+5dB SNR) were compared at baseline, three, and six months after ABF. The vowels involved were /a, i, u/, while the consonants were voiced /b, d, g/ and voiceless /p, t, k/ plosives. Speech pieces were presented at 30 dB SL in a sound-treated room through a loudspeaker positioned at 0° azimuth. Results: On average, the ABF maps shifted center frequency ranging from 0.46 semitones (0.04 octave) at (E12) to 23.94 semitones (1.99 octave) at (E1) as compared to the CBF maps. The mean vowel and consonant identification scores in quiet and in noise were significantly higher in ABF than in CBF (p<0.05) with a large effect size and the trend of improvement was seen with time. Voiced consonants had better scores than the voiceless consonants. Conclusion: The results demonstrated improved perception of vowels and consonants, particularly for sounds containing voicing cues after using the ABF maps. The results also suggested that ABF could be more effective for voice detection in noise. Overall, the findings indicate that correcting place mismatch with an ABF map may improve speech perception, at least among experienced adult cochlear implant users.

Upper and Lower Endoscopic Findings in Mesenteric Panniculitis Patients: A Case-Control Study

Background: The natural history and prognosis of mesenteric panniculitis (MP) are not well-described. Despite referral for colonoscopy being common for this indication, colonoscopy findings in MP patients have not been reported. Therefore, we aimed to describe upper and lower gastrointestinal (GI) endoscopy findings in patients with mesenteric panniculitis, compared to matched controls, to investigate their clinical outcomes including incidence of malignancy and mortality. Methods: Retrospective case–control study was conducted, and included patients who were diagnosed with mesenteric panniculitis according to Coulier radiologic criteria on abdominal computerized tomography between 1/2005 and 12/2019, and followed to 12/2021. The case group was compared to a matched control group without MP on abdominal CT. Clinical data and the upper and lower endoscopies’ reports were reviewed in both groups. We excluded patients who, beyond diagnosis of MP, were also diagnosed with current malignancy, significant intra-abdominal morbidity or inflammatory bowel disease. Results: The initial set of 376 patients with MP, after exclusion, included 187 patients. A total of 56.1% were male, with a mean age 60 ± 15 years. Of them, 74 (39%) patients underwent follow-up CT scans, which demonstrated, in 66 (89.2%) patients, a stable MP without any aggravation. Colonoscopy was performed in 89 MP patients, and 98/187 controls. No significant difference in the colonoscopies’ findings was found between the two groups. Gastroscopy was performed in 84 MP and 79 controls. No case of gastric cancer was found. No statistically significant difference was found in the rate of gastroscopy findings. By the end of the follow-up period, malignancy was diagnosed in four patients of the MP group. None were colon cancer. The mortality rate in the MP group was 3.2%, without a significant difference compared to the controls. None were MP related. Conclusions: MP identified on abdominal CT is not associated with pathologic endoscopy findings or future diagnosis of colon cancer, and also has no impact on mortality rate. Since repeating abdominal CT did not reveal any disease progression, the necessity of follow-up imaging for MP should be carefully reconsidered.

Perirenal Fat CT Radiomics-Based Survival Model for Upper Tract Urothelial Carcinoma: Integrating Texture Features with Clinical Predictors

Background: Upper tract urothelial carcinoma (UTUC) presents significant challenges in prognostication due to its rarity and complex anatomy. This study introduces a novel approach integrating perirenal fat (PRF) radiomics with clinical factors to enhance prognostic accuracy in UTUC. Methods: The study retrospectively analyzed 103 UTUC patients who underwent radical nephroureterectomy. PRF radiomics features were extracted from preoperative CT scans using a semi-automated segmentation method. Three prognostic models were developed: clinical, radiomics, and combined. Model performance was assessed using concordance index (C-index), time-dependent Area Under the Curve (AUC), and integrated Brier score. Results: The combined model demonstrated superior performance (C-index: 0.784, 95% CI: 0.707–0.861) compared to the radiomics (0.759, 95% CI: 0.678–0.840) and clinical (0.653, 95% CI: 0.547–0.759) models. Time-dependent AUC analysis revealed the radiomics model’s particular strength in short-term prognosis (12-month AUC: 0.9281), while the combined model excelled in long-term predictions (60-month AUC: 0.8403). Key PRF radiomics features showed stronger prognostic value than traditional clinical factors. Conclusions: Integration of PRF radiomics with clinical data significantly improves prognostic accuracy in UTUC. This approach offers a more nuanced analysis of the tumor microenvironment, potentially capturing early signs of tumor invasion not visible through conventional imaging. The semi-automated PRF segmentation method presents advantages in reproducibility and ease of use, facilitating potential clinical implementation.

Novel presentation of acalvaria with clavicular absence: A case report

Rationale: Acalvaria is an exceptionally rare congenital disorder marked by the absence of flat bones of the cranial vault, dura mater, and associated muscles, while the facial bones and base of the skull remain intact. Typically, the central nervous system is unaffected. Due to their extreme rarity, reported cases in the literature are infrequent. This condition often results in fatalities, as newborns with this anomaly generally have short life expectancies. However, there are a few documented cases of prolonged survival. Patient concerns: A 1-day-old full-term Palestinian male born to first-cousin parents at 37 + 6 weeks gestational age presented with an excessively soft skull without scalp abnormalities. The mother experienced polyhydramnios during the last 7 weeks of pregnancy. Diagnoses: Head ultrasound and X-rays confirmed the absence of skull vault bones and clavicles with normal facial bones. A CT scan showed well-formed brain structures and foci of hemorrhage in the left frontal lobe. Interventions: Supportive care was the primary management approach. The patient received comprehensive care in the neonatal intensive care unit, with a focus on stabilization and monitoring. Outcome: After 3 weeks in the neonatal intensive care unit, the patient showed normal feeding and function, but the prognosis remained poor. The patient’s family was informed about the poor prognosis. Lessons: This case reveals a unique combination of acalvaria and absent clavicles. Early antenatal diagnosis is essential but was delayed here. More research is needed to understand and improve the diagnosis of these conditions.

Material decomposition approaches for monosodium urate (MSU) quantification in gouty arthritis: a (bio)phantom study

BackgroundDual-energy computed tomography (DECT) is a noninvasive diagnostic tool for gouty arthritis. This study aimed to compare two postprocessing techniques for monosodium urate (MSU) detection: conventional two-material decomposition and material map-based decomposition.MethodsA raster phantom and an ex vivo biophantom, embedded with four different MSU concentrations, were scanned in two high-end CT scanners. Scanner 1 used the conventional postprocessing method while scanner 2 employed the material map approach. Volumetric analysis was performed to determine MSU detection, and image quality parameters, such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), were computed.ResultsThe material map-based method demonstrated superior MSU detection. Specifically, scanner 2 yielded total MSU volumes of 5.29 ± 0.28 mL and 4.52 ± 0.29 mL (mean ± standard deviation) in the raster and biophantom, respectively, versus 2.35 ± 0.23 mL and 1.15 ± 0.17 mL for scanner 1. Radiation dose correlated positively with detection for the conventional scanner, while there was no such correlation for the material map-based decomposition method in the biophantom. Despite its higher detection rate, material map-based decomposition was inferior in terms of SNR, CNR, and artifacts.ConclusionWhile material map-based decomposition resulted in superior MSU detection, it is limited by challenges such as increased artifacts. Our findings highlight the potential of this method for gout diagnosis while underscoring the need for further research to enhance its clinical reliability.Relevance statementAdvanced postprocessing such as material-map-based two-material decomposition might improve the sensitivity for gouty arthritis in clinical practice, thus, allowing for lower radiation doses or better sensitivity for gouty tophi.Key PointsDual-energy CT showed limited sensitivity for tophi with low MSU concentrations.Materiel-map-based decomposition increased sensitivity compared to conventional two-material decomposition.The advantages of material-map-based decomposition outweigh lower image quality and increased artifact load.Graphical

The effectiveness of deep learning model in differentiating benign and malignant pulmonary nodules on spiral CT

BACKGROUND: Pulmonary nodule, one of the most common clinical phenomena, is an irregular circular lesion with a diameter of ⩽ 3 cm in the lungs, which can be classified as benign or malignant. Differentiating benign and malignant pulmonary nodules has an essential effect on clinical medical diagnosis. OBJECTIVE: To explore the clinical value and diagnostic effects of the lung nodule classification and segmentation algorithm based on deep learning in differentiating benign and malignant pulmonary nodules. METHODS: A deep learning model with a fine-grained classification manner for the discrimination of pulmonary models in Dr.Wise Lung Analyzer. This study retrospectively enrolled 120 patients with pulmonary nodules detected by chest spiral CT from March 2021 to September 2022 in the radiology department of Ninghai First Hospital. The DL-based method and physicians’ accuracy, sensitivity, and specificity results were compared using the pathological results as the gold standard. The ROC curve of the deep learning model was plotted, and the AUCs were calculated. RESULTS: On 120 CT images, pathologically diagnosed 81 malignant nodules and 122 benign modules. The AUCs of radiologists’ diagnostic approach and DL-base method for differentiating patients were 0.62 and 0.81; radiologists’ diagnostic approach and DL-base method achieved AUCs of 0.75 and 0.90 for benign and malignant pulmonary nodules differentiate. The accuracy, sensitivity, and specificity with the deep learning model were 73.33%, 78.75%, and 62.50%, respectively, while the accuracy, sensitivity, and specificity with the physician’s diagnosis were 63.33%, 66.25%, and 57.500. CONCLUSION: There was no significant difference between the diagnosis results of the proposed DL-based method and the radiologists’ diagnostic approach in differentiating benign and malignant lung nodules on spiral CT (P< 0.05).

Comparing assisting technologies for proficiency in cardiac morphology: 3D printing and mixed reality versus CT slice images for morphological understanding of congenital heart defects by medical students

AbstractLearning cardiac morphology largely involves spatial abilities and studies indicate benefits from innovative 3D visualization technologies that speed up and increase the learning output. Studies comparing these teaching tools and their educational output are rare and few studies include complex congenital heart defects. This study compared the effects of 3D prints, mixed reality (MR) viewing of 3D meshes and standard cardiac CT slice images on medical students′ understanding of complex congenital heart defect morphology, measuring both objective level of understanding and subjective educational experience. The objective of this study was to compare morphological understanding and user experiences of 3D printed models, MR 3D visualization and axial 2D CT slices, in medical students examining morphological details in complex congenital heart defects. Medical students in the median 4th year of study (range 2nd to 6th) examined three of five different complex congenital heart defects by three different modalities: 3D printed model, MR viewed 3D mesh, and cardiac CT slices, answering a questionnaire on morphology and user experience. Time to complete task, diagnostic accuracy, and user experience data were collected and compared on group level. Task times were similar for all modalities. The percentage of correct answers was higher with MR visualization, which was also the preferred modality overall. Medical students both prefer and better understand the morphology of complex congenital heart disease with 3D models viewed using MR, without spending more time than with 3D prints or 2D CT images.

Saturation model for pore-type gas hydrate based on additional muddy conductive digital core

Abstract Original natural gas hydrate rock samples readily decompose under environmental changes during extraction, presenting challenges to conventional rock electrical analysis. This results in difficulty obtaining the cementation factor m and saturation exponent n of hydrate samples, thereby complicating the evaluation of hydrate saturation. Therefore, a method for revising the rock electrical parameters by digital core technology is proposed. Utilizing X-ray CT images of artificial gas hydrate samples, digital core models of natural gas hydrates were established. An erosion algorithm was employed to simulate the variation in mud content within the digital core, followed by the calculation of resistivity using the finite element method after meshing. Through analyzing the primary micro-pore structure parameters that influence the rock electrical parameters, the saturation model was subsequently refined. The results showed that the resistivity of hydrate digital core magnifies with increasing saturation of hydrate, tortuosity, and pore-throat ratio, but decreases with increasing coordination number and mud content. The rock electrical parameters were changed with the alteration of micro-pore structure. Based on the relationship between m, n, and micro-pore structure parameters, established a correction equation for them, further improved the Indonesian equation. The saturation of hydrate reservoir in Shenhu Sea area was evaluated using the modified Indonesian equation. The modified equation reduced the relative error from 34.8% to 15.6%, significantly enhanced the calculation accuracy.

Advanced Imaging Modalities in Cardiotoxicity: The Roles of Cardiac CT, MRI, and PET in Cardio-oncology

Advanced Imaging Modalities in Cardiotoxicity: The Roles of Cardiac CT, MRI, and PET in Cardio-oncology

CT image segmentation of foxtail millet seeds based on semantic segmentation model VGG16-UNet

Foxtail millet is an important minor cereal crop rich in nutrients. Due to the small size of its seeds, there is little information on the diversity of its seed structure among germplasms, limiting the identification of genes controlling seed development and germination. This paper utilized X-ray computed tomography (CT) scanning technology and deep learning models to reveal the microstructure of foxtail millet seeds, gaining insights into their internal features, distribution, and composition. A total of 100 foxtail millet varieties were scanned with X-ray computed tomography to obtain 3D reconstruction images and slices. Pre-processing steps were adopted to improve image segmentation accuracy, including noise reduction, rotation, contrast enhancement, and brightness enhancement. The experiment revealed that traditional OpenCV image processing methods failed to achieve precise segmentation, whereas deep learning models exhibited outstanding performance in segmenting seed CT slice images. We compared UNet, PSPNet, and DeepLabV3 models, selected different backbones and optimizers based on the dataset, and continuously adjusted learning rates and maximum training epochs to train the models. Results demonstrated that VGG16-UNet achieved an accuracy of 99.19% on the foxtail millet seed CT slice image dataset, outperforming PSPNet and DeepLabV3 models. Compared to ResNet-UNet, VGG16-UNet shows an improvement of approximately 3.18% in accuracy, demonstrating superior performance in accurately segmenting the inner glume, outer glume, embryo, and endosperm under various adhesion conditions. Accurate segmentation of foxtail millet CT images enables analysis of embryo size, endosperm size, and glume thickness, which impact germination, growth, and nutrition. This study fills a gap in small grain structure research, offering insights to optimize agriculture and molecular breeding for improved yield and quality.