International Journal of Computer Assisted Radiology and Surgery 
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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.Parameter-efficient framework for surgical action triplet recognition
ConclusionLeveraging effective structural design and robust capabilities of the foundational model, our proposed approach successfully strikes a balance between accuracy and computational efficiency. The source code is accessible athttps://github.com/Lycus99/LAM. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 30, 2024 Category: Intensive Care Source Type: research
LARLUS: laparoscopic augmented reality from laparoscopic ultrasound
ConclusionThe outcomes reveal promising results, suggesting the potential of LUS augmentation in surgical images to assist surgeons and serve as a training tool. We have used the LUS probe ’s shaft to disambiguate the rotational symmetry. However, in the long run, it would be desirable to find more convenient solutions. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 30, 2024 Category: Intensive Care Source Type: research
Fundamentals of Arthroscopic Surgery Training and beyond: a reinforcement learning exploration and benchmark
ConclusionThe presented benchmark enables the exploration of a novel reinforcement learning-based approach to skill performance assessment and in-procedure assistance for simulated surgical training scenarios. The evaluation protocol based on the learned reward model demonstrates potential for evaluating the performance of surgical trainees in simulation. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 29, 2024 Category: Intensive Care Source Type: research
Optimizing latent graph representations of surgical scenes for unseen domain generalization
ConclusionWe investigate the use of object-centric methods for unseen domain generalization, identify method-agnostic factors critical for performance, and present an optimized approach that substantially outperforms existing methods. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 28, 2024 Category: Intensive Care Source Type: research
One model to use them all: training a segmentation model with complementary datasets
ConclusionBy leveraging multiple datasets and applying mutual exclusion constraints, we developed a method that improves surgical scene segmentation performance without the need for fully annotated datasets. Our results demonstrate the feasibility of training a model on multiple complementary datasets. This paves the way for future work further alleviating the need for one specialized large, fully segmented dataset but instead the use of already existing datasets. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 27, 2024 Category: Intensive Care Source Type: research
Development of a universal cutting guide for raising deep circumflex iliac artery flaps
ConclusionReady-made cutting guides for the DCIA flap fit to the iliac crest and make quick and accurate flap raising possible while radiation dose and resources can be saved. The cutting guides fit sufficient to the iliac crest and should keep the advantages of a standard CAD planning. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 27, 2024 Category: Intensive Care Source Type: research
Design and evaluation of an anthropomorphic neck phantom for improved ultrasound diagnostics of thyroid gland tumors
ConclusionsThe proposed manufacturing technology offers a reliable and cost-effective approach to produce an anthropomorphic neck phantom for ultrasound diagnosis of the thyroid gland. The realistic simulation provided by the phantom enhances the quality and accuracy of ultrasound examinations, contributing to better training for medical professionals and improved patient care. Subsequent research efforts can concentrate on refining the fabrication process and exploring additional features to enhance the phantom ’s capabilities. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 26, 2024 Category: Intensive Care Source Type: research
Efficient EndoNeRF reconstruction and its application for data-driven surgical simulation
ConclusionWe have proposed a novel NeRF-based reconstruction framework with an emphasis on simulation purposes. Our reconstruction framework facilitates the efficient creation of high-quality surgical soft tissue 3D models. With multiple soft tissue simulations demonstrated, we show that our work has the potential to benefit downstream clinical tasks, such as surgical education. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 24, 2024 Category: Intensive Care Source Type: research
Laryngeal surface reconstructions from monocular endoscopic videos: a structure from motion pipeline for periodic deformations
ConclusionThe pre-filtering and featureless dense matching modules specialize the conventional SfM pipeline to handle the challenging laryngoscopic examinations, directly from patient videos. These 3D visualizations have the potential to improve spatial understanding of airway conditions. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 23, 2024 Category: Intensive Care Source Type: research
An investigation into augmentation and preprocessing for optimising X-ray classification in limited datasets: a case study on necrotising enterocolitis
ConclusionBased on an extensive validation of preprocessing and augmentation techniques, our work showcases the previously unreported potential of image preprocessing in AXR classification tasks with limited datasets. Our findings can be extended to other medical tasks for designing reliable classifier models with limited X-ray datasets. Ultimately, we also provide a benchmark for automated NEC detection and classification from AXRs. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 23, 2024 Category: Intensive Care Source Type: research
Stand in surgeon ’s shoes: virtual reality cross-training to enhance teamwork in surgery
ConclusionUntil now, VR applications for clinical training have focused on virtualizing existing curricula. We demonstrate how novel approaches which are not possible outside of a virtual environment, such as role swapping, may enhance the shared mental model of surgical teams by contextualizing each individual ’s role within the overall task in a time- and cost-efficient manner. As workflows grow increasingly sophisticated, we see VR curricula as being able to directly foster a shared model for success, ultimately benefiting patient outcomes through more effective teamwork in surgery. (Source: International Journal of C...
Source: International Journal of Computer Assisted Radiology and Surgery - April 20, 2024 Category: Intensive Care Source Type: research
From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery
ConclusionWe present a clinical evaluation of deep learning models trained for intraoperative tumor segmentation in breast-conserving surgery. We demonstrate that automatic contouring is limited in predicting pathology margins despite achieving high performance on quantitative metrics. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 20, 2024 Category: Intensive Care Source Type: research
EndoSRR: a comprehensive multi-stage approach for endoscopic specular reflection removal
ConclusionThe experimental results underscore the significance of proficient endoscopic specular reflection removal for enhancing visual perception and downstream tasks. The methodology and results presented in this study are poised to catalyze advancements in specular reflection removal, thereby augmenting the accuracy and safety of minimally invasive surgery. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 20, 2024 Category: Intensive Care Source Type: research
Design and navigation method of a soft robot for single-port transvesical radical prostatectomy
ConclusionsThe designed soft robot system, due to its soft structure, good flexibility, and accurate navigation, is expected to improve surgical safety and precision, thereby exhibiting significant potential for STRP. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 18, 2024 Category: Intensive Care Source Type: research
The development of a novel navigation system for reverse shoulder arthroplasty and its accuracy: a phantom and cadaveric study
ConclusionOur proposed optical navigation system successfully achieved real-time tracking of the surgical site, encompassing the patient phantom or cadaver and surgical instrument, thereby aiding surgeons in achieving precise surgical outcomes. Future study will explore the integration of robots to further enhance surgical efficiency and effectiveness. (Source: International Journal of Computer Assisted Radiology and Surgery)
Source: International Journal of Computer Assisted Radiology and Surgery - April 18, 2024 Category: Intensive Care Source Type: research
