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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018; 21st International C Alejandro F. Frangi,Julia A. Schnabel,Gabor

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書(shū)目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
副標(biāo)題21st International C
編輯Alejandro F. Frangi,Julia A. Schnabel,Gabor Fichti
視頻videohttp://file.papertrans.cn/630/629187/629187.mp4
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018; 21st International C Alejandro F. Frangi,Julia A. Schnabel,Gabor
描述.The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018...The 373 revised full papers presented were carefully reviewed and selected from 1068 submissions in a double-blind review process. The papers have been organized in the following topical sections: .Part I: Image Quality and Artefacts; Image Reconstruction Methods; Machine Learning in Medical Imaging; Statistical Analysis for Medical Imaging; Image Registration Methods. . Part II: .Optical and Histology Applications:. Optical Imaging Applications; Histology Applications; Microscopy Applications; Optical Coherence Tomography and Other Optical Imaging Applications. .Cardiac, Chest and Abdominal Applications:. Cardiac Imaging Applications: Colorectal, Kidney and Liver Imaging Applications; Lung Imaging Applications; Breast Imaging Applications; Other Abdominal Applications. .Part III: .Diffusion Tensor Imaging and Functional MRI:. Diffusion Tensor Imaging; Diffusion Weighted Imaging; Functional MRI; Human Connectome. .Neuroimaging and Brai
出版日期Conference proceedings 2018
關(guān)鍵詞Artificial intelligence; Classification; Computer vision; Estimation; Image analysis; Image enhancement; I
版次1
doihttps://doi.org/10.1007/978-3-030-00937-3
isbn_softcover978-3-030-00936-6
isbn_ebook978-3-030-00937-3Series 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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978-3-030-00936-6Springer Nature Switzerland AG 2018
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Learning from Noisy Label Statistics: Detecting High Grade Prostate Cancer in Ultrasound Guided Bioptainty that can lead to any possible misguidance during the biopsy procedure. In an . study with 155 patients, we analyze data from 250 suspicious cancer foci obtained during fusion biopsy. We achieve the average area under the curve of 0.84 for cancer grading and mean squared error of 0.12 in the estimation of tumor in biopsy core length.
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Respiratory Motion Modelling Using cGANsstates ahead of time. Experimental validations on three volunteer lung datasets demonstrate the potential of the proposed model both in terms of qualitative and quantitative results, and computational time required.
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Video-Based Computer Aided Arthroscopy for Patient Specific Reconstruction of the Anterior Cruciate urs reconstructed by touching the bone surface with an instrumented tool. Experimental validation using ex-vivo data shows that the method enables the accurate registration of the pre-operative model with the bone, providing useful information for guiding the surgeon during the medical procedure.
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Endoscopic Navigation in the Absence of CT Imagingo, we show that we are able to achieve submillimeter registrations in in-vivo clinical data and are able to assign confidence to these registrations using confidence criteria established using simulated data.
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