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Titlebook: Data Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis; First International Andrew Melbourne,Roxa

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发表于 2025-3-21 17:08:52 | 显示全部楼层 |阅读模式
书目名称Data Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis
副标题First International
编辑Andrew Melbourne,Roxane Licandro,Antonios Makropou
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Data Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis; First International  Andrew Melbourne,Roxa
描述.This book constitutes the refereed joint proceedings of the First International Workshop on Data Driven Treatment Response Assessment, DATRA 2018 and the Third International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.. The 5 full papers presented at DATRA 2018 and the 12 full papers presented at PIPPI 2018 were carefully reviewed and selected. .The DATRA  papers cover a wide range of exploring pattern recognition technologies for tackling clinical issues related to the follow-up analysis of medical data with focus on malignancy progression analysis, computer-aided models of treatment response, and anomaly detection in recovery feedback..The PIPPI papers cover topics of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infantand paediatric period..
出版日期Conference proceedings 2018
关键词Acoustics; Artificial intelligence; Biomarker analysis; Cancer research; Computer vision; Disease progres
版次1
doihttps://doi.org/10.1007/978-3-030-00807-9
isbn_softcover978-3-030-00806-2
isbn_ebook978-3-030-00807-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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Automatic Segmentation of Thigh Muscle in Longitudinal 3D T1-Weighted Magnetic Resonance (MR) Imagestesting interventions which are designed to maintain or improve muscle mass. The purpose of this paper is to report on an automated method of MRI-based thigh muscle segmentation framework that minimizes longitudinal deviation by using femur segmentation as a reference in a two-phase registration. Im
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Investigating Brain Age Deviation in Preterm Infants: A Deep Learning Approach), with an objective to investigate how differences in estimated brain age and PMA were associated with the risk of Cerebral Palsy disorders (CP). Infants were scanned up to 2 times, between 29 and 46 weeks (w) PMA. We applied a deep learning 2D convolutional neural network (CNN) regression model to
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Segmentation of Pelvic Vessels in Pediatric MRI Using a Patch-Based Deep Learning Approached MRI volume, a set of 2D axial patches are extracted using a limited number of user-selected landmarks. In order to take into account the volumetric information, successive 2D axial patches are combined together, producing a set of pseudo RGB color images. These RGB images are then used as input f
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