International Journal of Computer Assisted Radiology and Surgery This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Airway label prediction in video bronchoscopy: capturing temporal dependencies utilizing anatomical knowledge
ConclusionWe combine CNN-based single image classification of airway segments with anatomical constraints and temporal HMM-based inference for the first time. Our approach shows first promising results in vision-based guidance for bronchoscopy interventions in the absence of electromagnetic tracking and patient-specific CT scans. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 17, 2024 Category: Intensive Care Source Type: research

Deep learning-based osteochondritis dissecans detection in ultrasound images with humeral capitellum localization
ConclusionThis paper introduces a deep learning-based OCD classification method. The experimental results emphasize the effectiveness of focusing on the humeral capitellum for OCD classification in ultrasound images. Future work should involve evaluating the effectiveness of employing the proposed method by physicians during medical check-ups for OCD. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 17, 2024 Category: Intensive Care Source Type: research

Artificial intelligence-based image-domain material decomposition in single-energy computed tomography for head and neck cancer
ConclusionIn this study, we developed an AI-based material decomposition approach for head and neck cancer patients by introducing the loss function for MDIs via multiple keV-output learning. Our results suggest the feasibility of AI-based image-domain material decomposition in a conventional SECT system without a DECT scanner. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 14, 2024 Category: Intensive Care Source Type: research

Image-based hemodynamic simulations for intracranial aneurysms: the impact of complex vasculature
ConclusionBoth the magnitude and shape of the flow distribution vary depending on the model ’s complexity. The magnitude is primarily influenced by the global vessel model, while the shape is determined by the local structure. Furthermore, intra-aneurysmal flow strongly depends on the location in the vessel tree, emphasizing the need for complex model geometries for realistic hemodynamic assessment and rupture risk analysis. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 11, 2024 Category: Intensive Care Source Type: research

Endoscopic sleeve gastroplasty: stomach location and task classification for evaluation using artificial intelligence
ConclusionWe classified the four different stomach parts manipulated during the ESG procedure with 97% training accuracy and classified two repeated tasks with 99% training accuracy with images. We also classified the four parts of the stomach with a 99% training accuracy and two repeated tasks with a 100% training accuracy with video frames. This work will be essential in automating feedback mechanisms for learners in ESG. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 11, 2024 Category: Intensive Care Source Type: research

DeepPyramid+: medical image segmentation using Pyramid View Fusion and Deformable Pyramid Reception
ConclusionsDeepPyramid+ consistently outperforms state-of-the-art networks across diverse modalities considering different backbone networks, showcasing its versatility. Accordingly, DeepPyramid+ emerges as a robust and effective solution, successfully overcoming the intricate challenges associated with relevant content segmentation in medical images and surgical videos. Its consistent performance and adaptability indicate its potential to enhance precision in computerized medical image and surgical video analysis applications. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 8, 2024 Category: Intensive Care Source Type: research

Improved identification of tumors in 18F-FDG-PET examination by normalizing the standard uptake in the liver based on blood test data
ConclusionThe Z-score normalizes the mean and standard deviation. It is effective in ROC curve analysis and increases the clarity of the abnormality. This normalization is a key technique for effective measurement of maximum glucose consumption by tumors in the liver. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 5, 2024 Category: Intensive Care Source Type: research

Rapid detection of non-normal teeth on dental X-ray images using improved Mask R-CNN with attention mechanism
ConclusionThe proposed method enhances the accuracy and efficiency of abnormal tooth diagnosis for practitioners, while also facilitating early detection and treatment of dental caries to substantially lower patient costs. Additionally, it can enable rapid and objective evaluation of student performance in dental examinations. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 3, 2024 Category: Intensive Care Source Type: research

Development of an anatomical breast phantom from polyvinyl chloride plastisol with lesions of various shape, elasticity and echogenicity for teaching ultrasound examination
ConclusionThe proposed technology allows the creation of breast phantoms for practicing hand –eye coordination and develop the critical skills for navigation and assessment of the shape, margins, and size of the lesion, as well as performing an ultrasound-guided biopsy. It is cost-effective, reproducible, and easily implementable, and could be instrumental in generating ultrasonographers with crucial skills for accurate diagnosis of breast cancer, especially in low-resource settings. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 1, 2024 Category: Intensive Care Source Type: research

FAST skill assessment from kinematics data using convolutional neural networks
ConclusionsVariations in probe motion at different learning stages can be derived from kinematics data. These variations can be used for automatic and objective skill assessment without prior identification of clinical POIs. The proposed approach can improve the quality and objectivity of FAST proficiency evaluation. Furthermore, skill assessment combining ultrasound images and kinematics data can provide a more rigorous and diversified evaluation than using ultrasound images alone. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 1, 2024 Category: Intensive Care Source Type: research

Acknowledgement to reviewers
(Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - December 29, 2023 Category: Intensive Care Source Type: research

A novel pneumatic drill for bone biopsy under MRI imaging
ConclusionBoth drills worked well and were able to obtain comparable specimens. The pneumatic drill took slightly longer, 1.39  s on average, but this extra time would not be significant in clinical practice. We plan to use the pneumatic drill to enable MRI-safe bone biopsy for musculoskeletal lesions. Biopsy under MRI would provide excellent lesion visualization with no ionizing radiation. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - December 26, 2023 Category: Intensive Care Source Type: research

A semantic fidelity interpretable-assisted decision model for lung nodule classification
ConclusionThe experiments confirm that the methodology proposed can effectively capture the multi-scale features and contextual features of lung nodules. It enhances the capability of shallow structure drawing features in capsule networks, which in turn improves the classification performance of malignancy scores. The interpretable model can support the physicians ’ confidence in clinical decision-making. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - December 23, 2023 Category: Intensive Care Source Type: research

SGSR: style-subnets-assisted generative latent bank for large-factor super-resolution with registered medical image dataset
ConclusionSGSR performs large-factor SR while given a registered LR –HR medical image dataset with registration error for training. SGSR’s results have both realistic textures and accurate anatomical structures due to favorable quantitative and qualitative results. Experiments on multiple datasets demonstrated SGSR’s superiority over other SOTA methods. SR med ical images generated by SGSR are expected to improve the accuracy of pre-surgery diagnosis and reduce patient burden. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - December 21, 2023 Category: Intensive Care Source Type: research

Expanded tube attention for tubular structure segmentation
ConclusionsWe demonstrated that the proposed novel expanded tube attention module using thickened pseudo-labels can achieve easy-to-hard learning. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - December 19, 2023 Category: Intensive Care Source Type: research