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Computational Pathology and Ophthalmic Medical Image Analysis

First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 - 20, 2018, Proceedings

AvDanail Stoyanov,Zeike Taylor

Häftad, Engelska, 2018

Del 11039 i serien Lecture Notes in Computer Science

550 kr

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Beskrivning

This book constitutes the refereed joint proceedings of the First International Workshop on Computational Pathology, COMPAY 2018, and the 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 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 19 full papers (out of 25 submissions) presented at COMPAY 2018 and the 21 full papers (out of 31 submissions) presented at OMIA 2018 were carefully reviewed and selected. The COMPAY papers focus on artificial intelligence and deep learning. The OMIA papers cover various topics in the field of ophthalmic image analysis.

Produktinformation

Utgivningsdatum:2018-09-14
Mått:155 x 235 x 20 mm
Vikt:557 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:347
Förlag:Springer Nature Switzerland AG
ISBN:9783030009489

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Programmeringsböcker inom Data och IT

Innehållsförteckning

Improving Accuracy of Nuclei Segmentation by Reducing Histological Image Variability.- Multi-Resolution Networks for Semantic Segmentation in Whole Slide Images.- Improving High Resolution Histology Image Classification with Deep Spatial Fusion Network.- Construction of a Generative Model of H&E Stained Pathology Images of Pancreas Tumors Conditioned by a Voxel Value of MRI Image.- Accurate 3D reconstruction of a whole pancreatic cancer tumor from pathology images with different stains.- Role of Task Complexity and Training in Crowdsourced Image Annotation.- Capturing global spatial context for accurate cell classification in skin cancer histology.- Exploiting Multiple Color Representations to Improve Colon Cancer Detection in Whole Slide H&E Stains.- Leveraging Unlabeled Whole-Slide-Images for Mitosis Detection.- Evaluating Out-of-the-box Methods for the Classification of Hematopoietic Cells in Images of Stained Bone Marrow.- DeepCerv: Deep neural network for segmentation free robustcervical cell classification.- Whole slide image registration for the study of tumor heterogeneity.- Modality Conversion from Pathological Image to Ultrasonic Image Using Convolutional Neural Network.- Structure instance segmentation in renal tissue: a case study on tubular immune cell detection.- Cellular Community Detection for Tissue Phenotyping in Histology Images.- Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning.- Significance of Hyperparameter Optimization for Metastasis Detection in Breast Histology Images.- Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content.- Uncertainty Driven Pooling Network for Microvessel Segmentation in Routine Histology Images.- Ocular Structures Segmentation from Multi-sequences MRI using 3D Unet with Fully Connected CRFs.- Classification of Findings with Localized Lesions in Fundoscopic Images using a Regionally Guided CNN.- Segmentation of Corneal Nerves Using a U-Net-based Convolutional Neural Network.- Automatic Pigmentation Grading of the Trabecular Meshwork in Gonioscopic Images.- Large Receptive Field Fully Convolutional Network for Semantic Segmentation of Retinal Vasculature in Fundus Images.- Explaining Convolutional Neural Networks for Area Estimation of Choroidal Neovascularization via Genetic Programming.- Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning.- cGAN-based lacquer cracks segmentation in ICGA image.- Localizing Optic Disc and Cup for Glaucoma Screening via Deep Object Detection Networks.- Fundus Image Quality-guided Diabetic Retinopathy Grading.- DeepDisc: Optic Disc Segmentation based on Atrous Convolution and Spatial Pyramid Pooling.- Large-scale Left and Right Eye Classification in Retinal Images.- Automatic Segmentation of Cortex and Nucleus in Anterior Segment OCT Images.- Local Estimation of the Degree of Optic Disc Swelling from Color Fundus Photography.- Visual Field based Automatic Diagnosis of Glaucoma Using Deep Convolutional Neural Network.- Towards standardization of retinal vascular measurements: on the effect of image centering.- Feasibility study of Subfoveal Choroidal Thickness Changes in Spectral-Domain Optical Coherence Tomography Measurements of Macular Telangiectasia Type 2.- Segmentation of retinal layers in OCT images of the mouse eye utilizing polarization contrast.- Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation.- 2D Modeling and Correction of Fan-beam Scan Geometry in OCT.- A Bottom-up Saliency Estimation Approach for Neonatal Retinal Images.

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Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

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Understanding and Interpreting Machine Learning in Medical Image Computing Applications

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Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation

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Image Analysis for Moving Organ, Breast, and Thoracic Images

Danail Stoyanov, Zeike Taylor, Bernhard Kainz, Gabriel Maicas, Reinhard R. Beichel, Anne Martel, Lena Maier-Hein, Kanwal Bhatia, Tom Vercauteren, Ozan Oktay, Gustavo Carneiro, Andrew P. Bradley, Jacinto Nascimento, Hang Min, Matthew S. Brown, Colin Jacobs, Bianca Lassen-Schmidt, Kensaku Mori, Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Catarina Veiga

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Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities

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OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis

Danail Stoyanov, Zeike Taylor, Duygu Sarikaya, Jonathan McLeod, Miguel Angel González Ballester, Noel C.F. Codella, Anne Martel, Lena Maier-Hein, Anand Malpani, Marco A. Zenati, Sandrine De Ribaupierre, Luo Xiongbiao, Toby Collins, Tobias Reichl, Klaus Drechsler, Marius Erdt, Marius George Linguraru, Cristina Oyarzun Laura, Raj Shekhar, Stefan Wesarg, M. Emre Celebi, Kristin Dana, Allan Halpern

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Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

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Digital Pathology

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Fetal, Infant and Ophthalmic Medical Image Analysis

M. Jorge Cardoso, Tal Arbel, Andrew Melbourne, Hrvoje Bogunovic, Pim Moeskops, Xinjian Chen, Ernst Schwartz, Mona Garvin, Emma Robinson, Emanuele Trucco, Michael Ebner, Yanwu Xu, Antonios Makropoulos, Adrien Desjardin, Tom Vercauteren

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Ophthalmic Medical Image Analysis

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Computational Pathology and Ophthalmic Medical Image Analysis

First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 - 20, 2018, Proceedings

Beskrivning

Produktinformation

Utforska kategorier

Innehållsförteckning

Du kanske också är intresserad av

Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

Understanding and Interpreting Machine Learning in Medical Image Computing Applications

Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation

Image Analysis for Moving Organ, Breast, and Thoracic Images

Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities

OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Digital Pathology

Fetal, Infant and Ophthalmic Medical Image Analysis

Ophthalmic Medical Image Analysis

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