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.

CACTUSS: Common Anatomical CT-US Space for US examinations
Conclusion:CACTUSS provides a promising approach to improve US segmentation accuracy by leveraging CT labels, reducing the need for manual annotations. We generate IRs that inherit properties from both modalities while preserving the anatomical structure and are optimized for the task of aorta segmentation. Future work involves integrating CACTUSS into robotic ultrasound platforms for automated screening and conducting clinical feasibility studies. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 25, 2024 Category: Intensive Care Source Type: research

Design criteria for AI-based IT systems
DiscussionA fundamental question for the future remains whether society wants a quasi-wisdom-oriented healthcare system, based on data-driven intelligence with AI, or a human curated wisdom based on model-driven intelligence (with and without AI). Special CARS workshops and think tanks are planned to address this challenging question and possible new direction for assisting selected medical disciplines, e.g., radiology and surgery. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 25, 2024 Category: Intensive Care Source Type: research

Assessment of resectability of pancreatic cancer using novel immersive high-performance virtual reality rendering of abdominal computed tomography and magnetic resonance imaging
ConclusionVR enhanced visualisation of abdominal CT and MRI scan data provides intuitive handling and understanding of anatomy and might allow for more accurate staging of PDAC and could thus become a valuable adjunct in PDAC resectability assessment in the future. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 22, 2024 Category: Intensive Care Source Type: research

BDIS-SLAM: a lightweight CPU-based dense stereo SLAM for surgery
ConclusionThe proposed BDIS-SLAM is a lightweight stereo dense SLAM system for MIS. It achieves 30  Hz on a modern single-core CPU in typical endoscopy/colonoscopy scenarios (image size around\(640 \times 480\)). BDIS-SLAM provides a low-cost solution for dense mapping in MIS and has the potential to be applied in surgical robots and AR systems. Code is available athttps://github.com/JingweiSong/BDIS-SLAM. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 19, 2024 Category: Intensive Care Source Type: research

Domain transformation using semi-supervised CycleGAN for improving performance of classifying thyroid tissue images
ConclusionThe proposed method achieved the domain transformation of thyroid tissue images between two domains, where it retained the important features related to the classes across domains and showed the best F1 score with significant differences compared with other methods. In addition, the proposed method was further enhanced by addressing the class imbalance of the dataset. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 18, 2024 Category: Intensive Care Source Type: research

Design consideration on integration of mechanical intravascular ultrasound and electromagnetic tracking sensor for intravascular reconstruction
ConclusionPlacing the IVUS transducer on the proximal side of the EM sensor is superior in terms of interference reduction but inferior in terms of mechanical stability compared to a distal transducer. The distal side is preferred due to better mechanical stability during catheter manipulation at larger curvature. With this configuration, surface reconstruction errors less than 1.7  mm (with RMS 0.57 mm) were achieved when the distance to the field generator was less than 175 mm. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 18, 2024 Category: Intensive Care Source Type: research

Pose-based tremor type and level analysis for Parkinson ’s disease from video
ConclusionOur system offers a cost-effective PT classification and tremor severity estimation results as warning signs of PD for undiagnosed patients with PT symptoms. In addition, it provides a potential solution for supporting PD diagnosis in regions with limited clinical resources. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 18, 2024 Category: Intensive Care Source Type: research

Algorithmically designed flaps in tongue reconstruction: a feasibility analysis
ConclusionThe IFEM demonstrates significant potential as a tool for precise free flap design in tongue reconstruction surgeries. Its application could lead to improved surgical accuracy and better quality of life for patients undergoing such procedures. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 18, 2024 Category: Intensive Care Source Type: research

MAIRNet: weakly supervised anatomy-aware multimodal articulated image registration network
ConclusionIn summary, we developed a novel approach for multimodal articulated image registration. Comprehensive experiments conducted on three typical yet challenging datasets demonstrated the efficacy of the present approach. Our method achieved better results than the state-of-the-art approaches. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - January 18, 2024 Category: Intensive Care Source Type: research

Improved subcutaneous edema segmentation on abdominal CT using a generated adipose tissue density prior
ConclusionThe generated adipose tissue density prior improved edema segmentation accuracy. Accurate edema volume measurement may prove clinically useful. (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

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