CVMI21
* *Computer Vision for Microscopy Image Analysis
* 3D Fiber Segmentation with Deep Center Regression and Geometric Clustering
* Hierarchical Spatial Pyramid Network For Cervical Precancerous Segmentation By Reconstructing Deep Segmentation Networks
* Joint Spatial and Magnification Based Attention Framework for Large Scale Histopathology Classification, A
* Learning Melanocytic Proliferation Segmentation in Histopathology Images from Imperfect Annotations
* Quantifying Variability in Microscopy Image Analyses for COVID-19 Drug Discovery
* RCNN-SliceNet: A Slice and Cluster Approach for Nuclei Centroid Detection in Three-Dimensional Fluorescence Microscopy Images
* Unsupervised Detection of Cancerous Regions in Histology Imagery using Image-to-Image Translation
* X-net with Different Loss Functions for Cell Image Segmentation
9 for CVMI21
CVMI22
* *Computer Vision for Microscopy Image Analysis
* BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix
* Blood Vessel Segmentation from Low-Contrast and Wide-Field Optical Microscopic Images of Cranial Window by Attention-Gate-Based Network
* Cell Selection-based Data Reduction Pipeline for Whole Slide Image Analysis of Acute Myeloid Leukemia
* Ensemble Learning and Slice Fusion Strategy for Three-Dimensional Nuclei Instance Segmentation, An
* Fourier Image Transformer
* Multi stain graph fusion for multimodal integration in pathology
* Multi-Class Cell Detection Using Modified Self-Attention
* Self-Supervised Voxel-Level Representation Rediscovers Subcellular Structures in Volume Electron Microscopy
9 for CVMI22
CVMI23
* *Computer Vision for Microscopy Image Analysis
* Ensemble Method with Edge Awareness for Abnormally Shaped Nuclei Segmentation, An
* Fast Local Thickness
* Giga-SSL: Self-Supervised Learning for Gigapixel Images
* Learning to Correct Sloppy Annotations in Electron Microscopy Volumes
* New Bayesian Focal Loss Targeting Aleatoric Uncertainty Estimate: Pollen Image Recognition
* One-shot and Partially-Supervised Cell Image Segmentation Using Small Visual Prompt
* Out of Distribution Generalization via Interventional Style Transfer in Single-Cell Microscopy
* RxRx1: A Dataset for Evaluating Experimental Batch Correction Methods
* Super-Resolution Training Paradigm Based on Low-Resolution Data Only to Surpass the Technical Limits of STEM and STM Microscopy, A
* Theia: Bleed-Through Estimation with Convolutional Neural Networks
11 for CVMI23
CVMI24
* *Computer Vision for Microscopy Image Analysis
* Discovering interpretable models of scientific image data with deep learning
* Gene-Level Representation Learning via Interventional Style Transfer in Optical Pooled Screening
* Grad-CAMO: Learning Interpretable Single-Cell Morphological Profiles from 3D Cell Painting Images
* Histopathological Image Classification with Cell Morphology Aware Deep Neural Networks
* Low-Resolution-Only Microscopy Super-Resolution Models Generalizing to Non-Periodicities at Atomic Scale
* NOISe: Nuclei-Aware Osteoclast Instance Segmentation for Mouse-to-Human Domain Transfer
* Refining Biologically Inconsistent Segmentation Masks with Masked Autoencoders
* Super-resolution of biomedical volumes with 2D supervision
* Triage of 3D pathology data via 2.5D multiple-instance learning to guide pathologist assessments
* Uncertainty Estimation for Tumor Prediction with Unlabeled Data
* Unsupervised Microscopy Video Denoising
* Vim4Path: Self-Supervised Vision Mamba for Histopathology Images
* Weakly Supervised Set-Consistency Learning Improves Morphological Profiling of Single-Cell Images
14 for CVMI24