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Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

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Table of Contents

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    Book Overview
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    Chapter 1 Channel Embedding for Informative Protein Identification from Highly Multiplexed Images
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    Chapter 2 Demixing Calcium Imaging Data in C. elegans via Deformable Non-negative Matrix Factorization
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    Chapter 3 Automated Measurements of Key Morphological Features of Human Embryos for IVF
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    Chapter 4 A Novel Approach to Tongue Standardization and Feature Extraction
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    Chapter 5 Patch-Based Non-local Bayesian Networks for Blind Confocal Microscopy Denoising
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    Chapter 6 Attention-Guided Quality Assessment for Automated Cryo-EM Grid Screening
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    Chapter 7 MitoEM Dataset: Large-Scale 3D Mitochondria Instance Segmentation from EM Images
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    Chapter 8 Learning Guided Electron Microscopy with Active Acquisition
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    Chapter 9 Neuronal Subcompartment Classification and Merge Error Correction
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    Chapter 10 Microtubule Tracking in Electron Microscopy Volumes
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    Chapter 11 Leveraging Tools from Autonomous Navigation for Rapid, Robust Neuron Connectivity
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    Chapter 12 Statistical Atlas of C. elegans Neurons
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    Chapter 13 Probabilistic Joint Segmentation and Labeling of C. elegans Neurons
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    Chapter 14 Segmenting Continuous but Sparsely-Labeled Structures in Super-Resolution Microscopy Using Perceptual Grouping
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    Chapter 15 DISCo: Deep Learning, Instance Segmentation, and Correlations for Cell Segmentation in Calcium Imaging
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    Chapter 16 Isotropic Reconstruction of 3D EM Images with Unsupervised Degradation Learning
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    Chapter 17 Background and Illumination Correction for Time-Lapse Microscopy Data with Correlated Foreground
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    Chapter 18 Joint Spatial-Wavelet Dual-Stream Network for Super-Resolution
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    Chapter 19 Towards Neuron Segmentation from Macaque Brain Images: A Weakly Supervised Approach
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    Chapter 20 3D Reconstruction and Segmentation of Dissection Photographs for MRI-Free Neuropathology
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    Chapter 21 DistNet: Deep Tracking by Displacement Regression: Application to Bacteria Growing in the Mother Machine
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    Chapter 22 A Weakly Supervised Deep Learning Approach for Detecting Malaria and Sickle Cells in Blood Films
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    Chapter 23 Imaging Scattering Characteristics of Tissue in Transmitted Microscopy
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    Chapter 24 Attention Based Multiple Instance Learning for Classification of Blood Cell Disorders
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    Chapter 25 A Generative Modeling Approach for Interpreting Population-Level Variability in Brain Structure
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    Chapter 26 Processing-Aware Real-Time Rendering for Optimized Tissue Visualization in Intraoperative 4D OCT
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    Chapter 27 Boundary-Assisted Region Proposal Networks for Nucleus Segmentation
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    Chapter 28 BCData: A Large-Scale Dataset and Benchmark for Cell Detection and Counting
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    Chapter 29 Weakly-Supervised Nucleus Segmentation Based on Point Annotations: A Coarse-to-Fine Self-Stimulated Learning Strategy
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    Chapter 30 Structure Preserving Stain Normalization of Histopathology Images Using Self Supervised Semantic Guidance
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    Chapter 31 A Novel Loss Calibration Strategy for Object Detection Networks Training on Sparsely Annotated Pathological Datasets
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    Chapter 32 Histopathological Stain Transfer Using Style Transfer Network with Adversarial Loss
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    Chapter 33 Instance-Aware Self-supervised Learning for Nuclei Segmentation
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    Chapter 34 StyPath: Style-Transfer Data Augmentation for Robust Histology Image Classification
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    Chapter 35 Multimarginal Wasserstein Barycenter for Stain Normalization and Augmentation
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    Chapter 36 Corruption-Robust Enhancement of Deep Neural Networks for Classification of Peripheral Blood Smear Images
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    Chapter 37 Multi-field of View Aggregation and Context Encoding for Single-Stage Nucleus Recognition
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    Chapter 38 Self-supervised Nuclei Segmentation in Histopathological Images Using Attention
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    Chapter 39 FocusLiteNN: High Efficiency Focus Quality Assessment for Digital Pathology
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    Chapter 40 Pairwise Relation Learning for Semi-supervised Gland Segmentation
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    Chapter 41 Ranking-Based Survival Prediction on Histopathological Whole-Slide Images
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    Chapter 42 Renal Cell Carcinoma Detection and Subtyping with Minimal Point-Based Annotation in Whole-Slide Images
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    Chapter 43 Censoring-Aware Deep Ordinal Regression for Survival Prediction from Pathological Images
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    Chapter 44 Tracing Diagnosis Paths on Histopathology WSIs for Diagnostically Relevant Case Recommendation
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    Chapter 45 Weakly Supervised Multiple Instance Learning Histopathological Tumor Segmentation
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    Chapter 46 Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer
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    Chapter 47 Microscopic Fine-Grained Instance Classification Through Deep Attention
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    Chapter 48 A Deformable CRF Model for Histopathology Whole-Slide Image Classification
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    Chapter 49 Deep Active Learning for Breast Cancer Segmentation on Immunohistochemistry Images
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    Chapter 50 Multiple Instance Learning with Center Embeddings for Histopathology Classification
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    Chapter 51 Graph Attention Multi-instance Learning for Accurate Colorectal Cancer Staging
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    Chapter 52 Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment
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    Chapter 53 Modeling Histological Patterns for Differential Diagnosis of Atypical Breast Lesions
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    Chapter 54 Foveation for Segmentation of Mega-Pixel Histology Images
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    Chapter 55 Multimodal Latent Semantic Alignment for Automated Prostate Tissue Classification and Retrieval
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    Chapter 56 GREEN: a Graph REsidual rE-ranking Network for Grading Diabetic Retinopathy
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    Chapter 57 Combining Fundus Images and Fluorescein Angiography for Artery/Vein Classification Using the Hierarchical Vessel Graph Network
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    Chapter 58 Adaptive Dictionary Learning Based Multimodal Branch Retinal Vein Occlusion Fusion
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    Chapter 59 TR-GAN: Topology Ranking GAN with Triplet Loss for Retinal Artery/Vein Classification
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    Chapter 60 DeepGF: Glaucoma Forecast Using the Sequential Fundus Images
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    Chapter 61 Single-Shot Retinal Image Enhancement Using Deep Image Priors
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    Chapter 62 Robust Layer Segmentation Against Complex Retinal Abnormalities for e n face OCTA Generation
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    Chapter 63 Anterior Segment Eye Lesion Segmentation with Advanced Fusion Strategies and Auxiliary Tasks
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    Chapter 64 Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images
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    Chapter 65 Disentanglement Network for Unsupervised Speckle Reduction of Optical Coherence Tomography Images
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    Chapter 66 Positive-Aware Lesion Detection Network with Cross-scale Feature Pyramid for OCT Images
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    Chapter 67 Retinal Layer Segmentation Reformulated as OCT Language Processing
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    Chapter 68 Reconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT
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    Chapter 69 Open-Appositional-Synechial Anterior Chamber Angle Classification in AS-OCT Sequences
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    Chapter 70 A Macro-Micro Weakly-Supervised Framework for AS-OCT Tissue Segmentation
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    Chapter 71 Macular Hole and Cystoid Macular Edema Joint Segmentation by Two-Stage Network and Entropy Minimization
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    Chapter 72 Retinal Nerve Fiber Layer Defect Detection with Position Guidance
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    Chapter 73 An Elastic Interaction-Based Loss Function for Medical Image Segmentation
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    Chapter 74 Retinal Image Segmentation with a Structure-Texture Demixing Network
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    Chapter 75 BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation
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    Chapter 76 Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network
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    Chapter 77 RVSeg-Net: An Efficient Feature Pyramid Cascade Network for Retinal Vessel Segmentation
Attention for Chapter 4: A Novel Approach to Tongue Standardization and Feature Extraction
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Chapter title
A Novel Approach to Tongue Standardization and Feature Extraction
Chapter number 4
Book title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
Published by
Springer, Cham, October 2020
DOI 10.1007/978-3-030-59722-1_4
Book ISBNs
978-3-03-059721-4, 978-3-03-059722-1
Authors

Chenhao Wang, Camilla Cattaneo, Jing Liu, Wender Bredie, Ella Pagliarini, Jon Sporring, Wang, Chenhao, Cattaneo, Camilla, Liu, Jing, Bredie, Wender, Pagliarini, Ella, Sporring, Jon

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 33%
Unspecified 1 17%
Professor 1 17%
Professor > Associate Professor 1 17%
Unknown 1 17%
Readers by discipline Count As %
Unspecified 2 33%
Computer Science 1 17%
Agricultural and Biological Sciences 1 17%
Unknown 2 33%