Deeply Learnt Models :p
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Updated
Nov 13, 2016 - Python
Deeply Learnt Models :p
Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy via Likelihood Map Estimation by 3DCNN, in EMBC2020
Given an image of cells from a WSI, identify the mitotic figures and return a mitotic index.
Repository for mitosis detection using deep learning techniques
A project for detection of mitotic cells from tissue images using Computer Vision.
This repository contains a Python application using OpenCV for detecting mitosis in images. Aimed at researchers and biologists, it provides tools to automate the counting and identification of mitotic figures in microscopic images, supporting studies in cellular biology and medical diagnostics.
Automated tracking and interactive visualization/simulation of select cellular processes
The code base of the IXNAnalysis toolkit developed by the Joglekar Lab (main contributors: Chu Chen, Ajit Joglekar, and Rebekah Ronan)
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