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Titlebook: Computational Methods and Clinical Applications for Spine Imaging; 4th International Wo Jianhua Yao,Toma? Vrtovec,Shuo Li Conference procee

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發(fā)表于 2025-3-21 16:09:56 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging
副標(biāo)題4th International Wo
編輯Jianhua Yao,Toma? Vrtovec,Shuo Li
視頻videohttp://file.papertrans.cn/233/232690/232690.mp4
概述Includes supplementary material:
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Computational Methods and Clinical Applications for Spine Imaging; 4th International Wo Jianhua Yao,Toma? Vrtovec,Shuo Li Conference procee
描述This book constitutes the refereed proceedings of the 4th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.. . The 13 workshop papers were carefully reviewed and selected for inclusion in this volume. They aim at reviewing the state-of-the-art techniques, sharing the novel and emerging analysis and visualization techniques and discussing the clinical challenges and open problems in this rapidly growing field - including all major aspects of problems related to spine imaging, including clinical applications of spine imaging, computer aided diagnosis of spine conditions, computer aided detection of spine-related diseases, emerging computational imaging techniques for spinal diseases, fast 3D reconstruction of spine, feature extraction, multiscale analysis, pattern recognition, image enhancement of spine imaging, image-guided spine intervention and treatment, multimodal image registration and fusion for spine imaging, novel visualization techniques, segmentation techniques for spine imaging, statistical and geometric modeling for spine and verteb
出版日期Conference proceedings 2016
關(guān)鍵詞biomedical engineering; computer vision; computer-aided diagnosis; image analysis; visualization techniq
版次1
doihttps://doi.org/10.1007/978-3-319-55050-3
isbn_softcover978-3-319-55049-7
isbn_ebook978-3-319-55050-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2016
The information of publication is updating

書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging影響因子(影響力)




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging被引頻次




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging年度引用




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging年度引用學(xué)科排名




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging讀者反饋




書(shū)目名稱(chēng)Computational Methods and Clinical Applications for Spine Imaging讀者反饋學(xué)科排名




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What Is Clickbait? (Check All that Apply),east-squares regression. Despite its simplicity and without using specific domain knowledge, our approach achieves sub-voxel localisation accuracy of 0.61?mm, Dice segmentation overlaps of nearly 90% (for the training data) and takes less than ten minutes to process a new scan.
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發(fā)表于 2025-3-22 01:26:39 | 只看該作者
Michael R. Robinson,Moira M. Fergusonral bodies of the thoracic and lumbar spine. We evaluated osteophyte detection performance on 45 individuals with 5-fold cross validation and achieved state-of-the-art performance with 85% sensitivity at 2 false positive detections per patient.
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G. T. O. Lebreton,F. W. (Bill) H. Beamishenerate the patient’s specified 3D model. This method just needs one prior model for 3D reconstruction. The experiments on nine vertebrae of three patients show the average reconstruction error is 1.2?mm (1.0?mm–1.3?mm) which is comparable to the state of the art.
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Operator Theory: Advances and Applications on Grassmannian kernels in order to assess the similarity between shape topology and inter-vertebral poses in both groups (P, NP). We test the method to classify 52 progressive and 81 non-progressive patients enrolled in a prospective clinical study, yielding classification rates comparing favorably to standard classification methods.
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Accurate Intervertebral Disc Localisation and Segmentation in MRI Using Vantage Point Hough Forests east-squares regression. Despite its simplicity and without using specific domain knowledge, our approach achieves sub-voxel localisation accuracy of 0.61?mm, Dice segmentation overlaps of nearly 90% (for the training data) and takes less than ten minutes to process a new scan.
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發(fā)表于 2025-3-22 23:19:49 | 只看該作者
Detection of Degenerative Osteophytes of the Spine on PET/CT Using Region-Based Convolutional Neuralral bodies of the thoracic and lumbar spine. We evaluated osteophyte detection performance on 45 individuals with 5-fold cross validation and achieved state-of-the-art performance with 85% sensitivity at 2 false positive detections per patient.
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Classification of Progressive and Non-progressive Scoliosis Patients Using Discriminant Manifolds on Grassmannian kernels in order to assess the similarity between shape topology and inter-vertebral poses in both groups (P, NP). We test the method to classify 52 progressive and 81 non-progressive patients enrolled in a prospective clinical study, yielding classification rates comparing favorably to standard classification methods.
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