deep_semantic_histology: Deep Semantic Representations for Cancer Histology Images
Project description
Overview
deep_semantic_representation is a python library to apply tissue/cell segmentation models for histology images (bioRxiv, 2022). Fucntions for plotting the distribution are also implemented.
Installation
The package can be installed with pip:
$ pip install deepsemantic
Prerequisites
Python version 3.6 or newer.
numpy >=1.20.3
joblib >=0.13.2
Pillow >=8.0.1
nmslib >=2.0.6
matplotlib >= 3.5.0
scikit-learn >=1.1.0
seaborn >=0.10.1
pandas >=1.1.0
cv2
Recommended Environment
- OS
Linux
Mac
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC-BY-NC-SA 4.0)
For non-commercial use, please use the code under CC-BY-NC-SA.
If you would like to use the code for commercial purposes, please contact us <ishum-prm@m.u-tokyo.ac.jp>.
Citation
If you use this library for your research, please cite:
Komura, D., Kawabe, A., Fukuta, K., Sano, K., Umezaki, T., Koda, H., Suzuki, R., Tominaga, K., Ochi, M., Konishi, H., Masakado, F., Saito, N., Sato, Y., Onoyama, T., Nishida, S., Furuya, G., Katoh, H., Yamashita, H., Kakimi, K., Seto, Y., Ushiku, T., Fukayama, M., Ishikawa, S.,
“Universal encoding of pan-cancer histology by deep texture representations.”
Cell Reports 38, 110424,2022. https://doi.org/10.1016/j.celrep.2022.110424
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for deepsemhist-0.0.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | fac278abe93650beaf0f58880c8865a92e0a005470f067f4cb7bc150dbfc9ea9 |
|
MD5 | c6b45e29117231d42831ae4f583fb298 |
|
BLAKE2b-256 | 64f45e04d87aea8733810338476c155c4c954d1053d770a9b3f5fe013265ac89 |