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201103 ||| eng |
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|a 9783030597221
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| 100 |
1 |
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|a Martel, Anne L.
|e [editor]
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| 245 |
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|a Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
|h Elektronische Ressource
|b 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part V
|c edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz
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| 250 |
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|a 1st ed. 2020
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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| 300 |
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|a XXXVII, 811 p. 11 illus
|b online resource
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| 505 |
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|a Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network -- RVSeg-Net: an Efficient Feature Pyramid Cascade Network for Retinal Vessel Segmentation-
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| 505 |
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|a Probabilistic Segmentation and Labeling of C. elegans Neurons -- Segmenting Continuous but Sparsely-Labeled Structures in Super-Resolution Microscopy Using Perceptual Grouping -- DISCo: Deep learning, Instance Segmentation, and Correlations for cell segmentation in calcium imaging -- Isotropic Reconstruction of 3D EM Images with Unsupervised Degradation Learning -- Background and illumination correction for time-lapse microscopy data with correlated foreground -- Joint Spatial-Wavelet Dual-Stream Network for Super-Resolution -- Towards Neuron Segmentation from Macaque Brain Images: A Weakly Supervised Approach -- 3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology -- DistNet: Deep Tracking by displacement regression: application to bacteria growing in the Mother Machine -- A weakly supervised deep learning approach for detecting malaria and sickle cell anemia in blood films --
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| 505 |
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|a Biological, Optical, Microscopic Imaging -- Channel Embedding for Informative Protein Identification from Highly Multiplexed Images -- Demixing Calcium Imaging Data in C. elegans via Deformable Non-negative Matrix Factorization -- Automated Measurements of Key Morphological Features of Human Embryos for IVF -- A Novel Approach to Tongue Standardization and Feature Extraction -- Patch-based Non-Local Bayesian Networks for Blind Confocal Microscopy Denoising -- Attention-guided Quality Assessment for Automated Cryo-EM Grid Screening -- MitoEM Dataset: Large-scale 3D Mitochondria Instance Segmentation from EM Images -- Learning Guided Electron Microscopy with Active Acquisition -- Neuronal Subcompartment Classification and Merge Error Correction -- Microtubule Tracking in Electron Microscopy Volumes -- Leveraging Tools from Autonomous Navigation for Rapid, Robust Neuron Connectivity -- Statistical Atlas of C.elegans Neurons --
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| 505 |
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|a Instance-aware Self-supervised Learning for Nuclei Segmentation -- StyPath: Style-Transfer Data Augmentation For Robust Histology Image Classification -- Multimarginal Wasserstein Barycenter for Stain Normalization and Augmentation -- Corruption-Robust Enhancement of Deep Neural Networks for Classification of Peripheral Blood Smear Images -- Multi-Field of View Aggregation and Context Encoding for Single-Stage Nucleus Recognition -- Self-Supervised Nuclei Segmentation in Histopathological Images Using Attention -- FocusLiteNN: High Efficiency Focus Quality Assessment for Digital Pathology -- Histopathology Image Analysis -- Pairwise Relation Learning for Semi-supervised Gland Segmentation -- Ranking-Based Survival Prediction on Histopathological Whole-Slide Images -- Renal Cell Carcinoma Detection and Subtyping with Minimal Point-Based Annotation in Whole-Slide Images -- Censoring-Aware Deep Ordinal Regression for Survival Prediction from Pathological Images --
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| 505 |
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|a Tracing Diagnosis Paths on Histopathology WSIs for Diagnostically Relevant Case Recommendation -- Weakly supervised multiple instance learning histopathological tumor segmentation -- Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer -- Microscopic fine-grained instance classification through deep attention -- A Deformable CRF Model for Histopathology Whole-slide Image Classification -- Deep Active Learning for Breast Cancer Segmentation on Immunohistochemistry Images -- Multiple Instance Learning with Center Embeddings for Histopathology Classification -- Graph Attention Multi-instance Learning for Accurate Colorectal Cancer Staging -- Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment -- Modeling Histological Patterns for Differential Diagnosis of Atypical Breast Lesions -- Foveation for Segmentation of Mega-pixel Histology Images --
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| 505 |
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|a Disentanglement Network for Unpsupervised Speckle Reduction of Optical Coherence Tomography Images -- Positive-Aware Lesion Detection Network with Cross-scale Feature Pyramid for OCT Images -- Retinal Layer Segmentation Reformulated as OCT Language Processing -- Reconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT -- Open-Appositional-Synechial Anterior Chamber Angle Classification in AS-OCT Sequences -- A Macro-Micro Weakly-supervised Framework for AS-OCT Tissue Segmentation -- Macular Hole and Cystoid Macular Edema Joint Segmentation by Two-Stage Network and Entropy Minimization -- Retinal Nerve Fiber Layer Defect Detection With Position Guidance -- An Elastic Interaction Based-Loss Function for Medical Image Segmentation -- Retinal Image Segmentation with a Structure-Texture Demixing Network -- BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation --
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| 505 |
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|a Imaging Scattering Characteristics of Tissue in Transmitted Microscopy -- Attention based multiple instance learning for classification of blood cell disorders -- A generative modeling approach for interpreting population-level variability in brain structure -- Processing-Aware Real-Time Rendering for Optimized Tissue Visualization in Intraoperative 4D OCT -- Cell Segmentation and Stain Normalization -- Boundary-assisted Region Proposal Networks for Nucleus Segmentation -- BCData: A Large-Scale Dataset and Benchmark for Cell Detection and Counting -- Weakly-Supervised Nucleus Segmentation Based on Point Annotations: A Coarse-to-Fine Self-Stimulated Learning Strategy -- Structure Preserving Stain Normalization of Histopathology Images Using Self Supervised Semantic Guidance -- A Novel Loss Calibration Strategy for Object Detection Networks Training on Sparsely Annotated Pathological Datasets -- Histopathological Stain Transfer Using Style Transfer Network With Adversarial Loss --
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| 505 |
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|a Multimodal Latent Semantic Alignment for Automated Prostate Tissue Classification and Retrieval -- Opthalmology -- GREEN: a Graph REsidual rE-ranking Network for Grading Diabetic Retinopathy -- Combining Fundus Images and Fluorescein Angiographyfor Artery/Vein Classification Using the Hierarchical Vessel Graph Network -- Adaptive Dictionary Learning Based Multimodal Branch Retinal Vein Occlusion Fusion -- TR-GAN: Topology Ranking GAN with Triplet Loss for Retinal Artery/Vein Classification -- DeepGF: Glaucoma Forecast Using Sequential Fundus Images -- Single-Shot Retinal Image Enhancement Using Deep Image Prior -- Robust Layer Segmentation against Complex Retinal Abnormalities for en face OCTA Generation -- Anterior Segment Eye Lesion Segmentation with Advanced Fusion Strategies and Auxiliary Tasks -- Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images --
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| 653 |
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|a Computers and Education
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| 653 |
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|a Computer vision
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| 653 |
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|a Computer Application in Social and Behavioral Sciences
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| 653 |
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|a Social sciences / Data processing
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| 653 |
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|a Education / Data processing
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Automated Pattern Recognition
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| 653 |
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|a Pattern recognition systems
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Computer Vision
|
| 700 |
1 |
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|a Abolmaesumi, Purang
|e [editor]
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| 700 |
1 |
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|a Stoyanov, Danail
|e [editor]
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| 700 |
1 |
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|a Mateus, Diana
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics
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| 028 |
5 |
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|a 10.1007/978-3-030-59722-1
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-030-59722-1?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 006.37
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| 520 |
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|a The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography
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