MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention 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.

Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration
In this study, we propose a mean-teacher based registration framework, which incorporates an additional temporal consistency regularization term by encouraging the teacher model's prediction to be consistent with that of the student model. More importantly, instead of searching for a fixed weight, the teacher enables automatically adjusting the weights of the spatial regularization and the temporal consistency regularization by taking advantage of the transformation uncertainty and appearance uncertainty. Extensive experiments on the challenging abdominal CT-MRI registration show that our training strategy can promisingly ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 30, 2023 Category: Radiology Authors: Zhe Xu Jie Luo Donghuan Lu Jiangpeng Yan Sarah Frisken Jayender Jagadeesan William M Wells Xiu Li Yefeng Zheng Raymond Kai-Yu Tong Source Type: research

On Surgical Planning of Percutaneous Nephrolithotomy with Patient-Specific CTRs
Med Image Comput Comput Assist Interv. 2022 Sep;13437:626-635. doi: 10.1007/978-3-031-16449-1_60. Epub 2022 Sep 17.ABSTRACTPercutaneous nephrolithotomy (PCNL) is considered a first-choice minimally invasive procedure for treating kidney stones larger than 2 cm. It yields higher stone-free rates than other minimally invasive techniques and is employed when extracorporeal shock wave lithotripsy or uteroscopy are, for instance, infeasible. Using this technique, surgeons create a tract through which a scope is inserted for gaining access to the stones. Traditional PCNL tools, however, present limited maneuverability, may requi...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 30, 2023 Category: Radiology Authors: Filipe C Pedrosa Navid Feizi Ruisi Zhang Remi Delaunay Dianne Sacco Jayender Jagadeesan Rajni Patel Source Type: research

USPoint: Self-Supervised Interest Point Detection and Description for Ultrasound-Probe Motion Estimation During Fine-Adjustment Standard Fetal Plane Finding
Med Image Comput Comput Assist Interv. 2022 Sep 17;2022:104-114. doi: 10.1007/978-3-031-16449-1_11.ABSTRACTUltrasound (US)-probe motion estimation is a fundamental problem in automated standard plane locating during obstetric US diagnosis. Most recent existing recent works employ deep neural network (DNN) to regress the probe motion. However, these deep regressionbased methods leverage the DNN to overfit on the specific training data, which is naturally lack of generalization ability for the clinical application. In this paper, we are back to generalized US feature learning rather than deep parameter regression. We propose...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 24, 2023 Category: Radiology Authors: Cheng Zhao Richard Droste Lior Drukker Aris T Papageorghiou J Alison Noble Source Type: research

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research

Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data
Med Image Comput Comput Assist Interv. 2022 Sep;13431:113-122. doi: 10.1007/978-3-031-16431-6_11. Epub 2022 Sep 15.ABSTRACTAdvanced contemporary diffusion models for tissue microstructure often require diffusion MRI (DMRI) data with sufficiently dense sampling in the diffusion wavevector space for reliable model fitting, which might not always be feasible in practice. A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely sampled data. However, existing methods are either agnostic to the data geometry in the diffusion wavevector space ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Geng Chen Haotian Jiang Jiannan Liu Jiquan Ma Hui Cui Yong Xia Pew-Thian Yap Source Type: research