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.- 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.- 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.- 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.- Tracing Diagnosis Paths on Histopathology WSIs for Diagnostically Relevant Case Recommendation.- Weakly supervised multiple instance learning histopathological tumor segmentation.- Divide-and-Rul