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Titlebook: Clinical Image-Based Procedures; 13th International W Klaus Drechsler,Cristina Oyarzun Laura,Marius Erdt Conference proceedings 2024 The Ed

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发表于 2025-3-21 19:14:50 | 显示全部楼层 |阅读模式
书目名称Clinical Image-Based Procedures
副标题13th International W
编辑Klaus Drechsler,Cristina Oyarzun Laura,Marius Erdt
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Clinical Image-Based Procedures; 13th International W Klaus Drechsler,Cristina Oyarzun Laura,Marius Erdt Conference proceedings 2024 The Ed
描述.This book constitutes the proceedings of the 13th Workshop on Clinical Image-Based Procedures, CLIP 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco in October 2024...The 9 full papers included in this book were carefully reviewed and selected from 11 submissions. They deal with Clinical image-based procedures, focusing on holistic patient models as an important step towards personalized healthcare. .
出版日期Conference proceedings 2024
关键词Medical Imaging; Translational Research; Segmentation; Registration; Preoperative Planning; Clinical Proc
版次1
doihttps://doi.org/10.1007/978-3-031-73083-2
isbn_softcover978-3-031-73082-5
isbn_ebook978-3-031-73083-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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,Enhancing Image Classification in Small and Unbalanced Datasets Through Synthetic Data Augmentation and present high imbalance between target classes. Considering that data acquisition is not always feasible, especially for underrepresented classes, our approach introduces a novel synthetic augmentation strategy using class-specific Variational Autoencoders (VAEs) and latent space interpolation t
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,HTSeg: Hybrid Two-Stage Segmentation Framework for Intestine Segmentation from CT Volumes,training to reduce the labor of manually annotating intestines. The proposed Hybrid Two-stage Segmentation (HTSeg) framework consists of two networks, a 2D swin-transformer-based network as the first stage and a 3D network as the second stage. In the first stage, we use 6964 labeled CT slices to tra
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,EnPrO: Enhancing Precision Through Optimization in Image-Guided Spine Surgical Procedures,(IGSS) procedures. The proposed research provides a novel technique for improving precision in IGSS via EnPrO by refining the mapping of 2D fluoroscopic images to the patient’s anatomy. The fundamental strategy is to minimize reprojection error (RPE) by picking optimal fiducial sites via weighted no
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Conference proceedings 2024included in this book were carefully reviewed and selected from 11 submissions. They deal with Clinical image-based procedures, focusing on holistic patient models as an important step towards personalized healthcare. .
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