BCCD (Blood Cell Count and Detection) Dataset is a small-scale dataset for blood cells detection.
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Updated
Sep 16, 2021 - Python
BCCD (Blood Cell Count and Detection) Dataset is a small-scale dataset for blood cells detection.
nucleus/cell and histopathology image classification,detection,segmentation
Automated 3D cell detection in very large images
Instance Segmentation with PyTorch & PyTorch Lightning.
Standalone cellfinder cell detection algorithm
OCELOT 2023: Cell Detection from Cell-Tissue Interaction
Efficient cell detection in large images using cellfinder in napari
Visualisation and analysis of brain imaging data
[IMAVIS] Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".
MagellanMapper is a graphical interface for 3D bioimage annotation, atlas registration, and regional quantification
Harness deep learning and bounding boxes to perform object detection, segmentation, tracking and more.
Detecting and Tracking cancer (HeLa) cells using Computer Vision techniques. The project also detects cell division and analyses cell motion such as speed, distance travelled etc. The project uses OpenCV3 for image processing.
Cell detection in holographic images.
SAM on medical images based on https://github.com/facebookresearch/segment-anything
Соревнование бинарной классификации на Kaggle
Approach that won 3rd place in the OCELOT 2023 Challenge. Multi-organ H&E-based deep learning model for cell detection, applicable for tumor cellularity/ purity/ content estimation.
Haar feature-based cascade classifier to detect infected cells with Malaria
Cell Detection and Cell Segmentation
Region-based Fitting of Overlapping Ellipses (original implementation by C. Panagiotakis and A.A. Argyros, Image Vis Comput 2020)
SuperDSM is a globally optimal segmentation method based on superadditivity and deformable shape models for cell nuclei in fluorescence microscopy images and beyond.
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