000 08470nam a22007695i 4500
001 978-3-030-00949-6
003 DE-He213
005 20240730202455.0
007 cr nn 008mamaa
008 180913s2018 sz | s |||| 0|eng d
020 _a9783030009496
_9978-3-030-00949-6
024 7 _a10.1007/978-3-030-00949-6
_2doi
050 4 _aTA1634
072 7 _aUYQV
_2bicssc
072 7 _aCOM016000
_2bisacsh
072 7 _aUYQV
_2thema
082 0 4 _a006.37
_223
245 1 0 _aComputational Pathology and Ophthalmic Medical Image Analysis
_h[electronic resource] :
_bFirst International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 - 20, 2018, Proceedings /
_cedited by Danail Stoyanov, Zeike Taylor, Francesco Ciompi, Yanwu Xu, Anne Martel, Lena Maier-Hein, Nasir Rajpoot, Jeroen van der Laak, Mitko Veta, Stephen McKenna, David Snead, Emanuele Trucco, Mona K. Garvin, Xin Jan Chen, Hrvoje Bogunovic.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXVII, 347 p. 135 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v11039
505 0 _aImproving 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.
520 _aThis 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.
650 0 _aComputer vision.
_9171589
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer arithmetic and logic units.
_936750
650 0 _aComputer science
_xMathematics.
_93866
650 0 _aMathematical statistics.
_99597
650 0 _aPattern recognition systems.
_93953
650 1 4 _aComputer Vision.
_9171590
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aArithmetic and Logic Structures.
_936752
650 2 4 _aProbability and Statistics in Computer Science.
_931857
650 2 4 _aAutomated Pattern Recognition.
_931568
700 1 _aStoyanov, Danail.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171591
700 1 _aTaylor, Zeike.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171592
700 1 _aCiompi, Francesco.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171593
700 1 _aXu, Yanwu.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171594
700 1 _aMartel, Anne.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171595
700 1 _aMaier-Hein, Lena.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171596
700 1 _aRajpoot, Nasir.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171597
700 1 _avan der Laak, Jeroen.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171598
700 1 _aVeta, Mitko.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171599
700 1 _aMcKenna, Stephen.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171600
700 1 _aSnead, David.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171601
700 1 _aTrucco, Emanuele.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171602
700 1 _aGarvin, Mona K.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171603
700 1 _aChen, Xin Jan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171604
700 1 _aBogunovic, Hrvoje.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9171605
710 2 _aSpringerLink (Online service)
_9171606
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030009489
776 0 8 _iPrinted edition:
_z9783030009502
830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v11039
_9171607
856 4 0 _uhttps://doi.org/10.1007/978-3-030-00949-6
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c97033
_d97033