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Titlebook: Clinical Image-Based Procedures; 11th Workshop, CLIP Yufei Chen,Marius George Linguraru,Cristina Oyarzu Conference proceedings 2023 The Ed

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11#
發(fā)表于 2025-3-23 13:02:10 | 只看該作者
0302-9743 ocus on the applicability of basic research methods in the clinical practice by creating holistic patient models as an important step towards personalized healthcare.?.978-3-031-23178-0978-3-031-23179-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
12#
發(fā)表于 2025-3-23 15:49:16 | 只看該作者
Conference proceedings 202322, in Singapore in September 2022.?The 9 full papers included in this book were carefully reviewed and selected from 12 submissions. They focus on the applicability of basic research methods in the clinical practice by creating holistic patient models as an important step towards personalized healthcare.?.
13#
發(fā)表于 2025-3-23 20:30:33 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/228004.jpg
14#
發(fā)表于 2025-3-24 01:07:08 | 只看該作者
Clinical Image-Based Procedures978-3-031-23179-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
15#
發(fā)表于 2025-3-24 05:31:57 | 只看該作者
16#
發(fā)表于 2025-3-24 08:21:15 | 只看該作者
17#
發(fā)表于 2025-3-24 13:54:14 | 只看該作者
Mexico in the New Emerging World Orderdied in preoperative settings. In intraoperative imaging, the utility of DRRs is limited by the challenges in generating them in real-time and supporting optimization procedures that rely on repeated DRR synthesis. While immense progress has been made in accelerating the generation of DRRs through a
18#
發(fā)表于 2025-3-24 17:53:36 | 只看該作者
19#
發(fā)表于 2025-3-24 20:38:44 | 只看該作者
Rural Latin America in Transition been a lot of medical research in the field to detect joint inflammation utilising NIR-FOI, an objective machine learning based evaluation method of the image data has not been developed, yet..The measured NIR-FOI data consists of two spatial dimensions (image pixel) and one temporal dimension. To
20#
發(fā)表于 2025-3-25 01:59:32 | 只看該作者
Rural Latin America in Transitiond allowed for efficient workflows in clinical settings. Accurate automatic identification of dental landmarks in IOS is required to aid dental researchers and clinicians to plan and assess tooth position for crown restorations, orthodontics movements, and/or implant dentistry. In this paper, we pres
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