Skip to content

Source code for the 2021 ICASSP paper "Acute Lymphoblastic Leukemia detection based on adaptive unsharpening and Deep Learning"

License

Notifications You must be signed in to change notification settings

AngeloUNIMI/CNN-ALL

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

CNN-ALL

Matlab source code for the paper:

A. Genovese, M. S. Hosseini, V. Piuri, K. N. Plataniotis, and F. Scotti, 
"Acute Lymphoblastic Leukemia detection based on adaptive unsharpening and Deep Learning", 
in Proc. of the 2021 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP 2021), 
Toronto, ON, Canada, June 6-11, 2021, pp. 1205-1209. 
ISBN: 978-1-7281-7605-5. [DOI: 10.1109/ICASSP39728.2021.9414362]

Paper:

https://ieeexplore.ieee.org/document/9414362

Project page:

https://iebil.di.unimi.it/cnnALL/index.htm

Outline: Outline

Citation:

@InProceedings {icassp21,
author = {A. Genovese and M. S. Hosseini and V. Piuri and K. N. Plataniotis and F. Scotti},
booktitle = {Proc. of the 2021 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP 2021)},
title = {Acute Lymphoblastic Leukemia detection based on adaptive unsharpening and Deep Learning},
address = {Toronto, ON, Canada},
pages = {1205-1209},
month = {June},
day = {6-11},
year = {2021},
note = {978-1-7281-7605-5}
}

Main files:

- launch_VARPCANet: main file

Required files:

- ./imgs/orig/ALL-IDB/ALL_IDB2/img: Database of images, with filenames in the format "Im001_1.tif", 
the images can be downloaded at: https://homes.di.unimi.it/scotti/all/

Part of the code uses the Matlab source code of the paper:

T. Chan, K. Jia, S. Gao, J. Lu, Z. Zeng and Y. Ma, 
"PCANet: A Simple Deep Learning Baseline for Image Classification?," 
in IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5017-5032, Dec. 2015.
DOI: 10.1109/TIP.2015.2475625
http://mx.nthu.edu.tw/~tsunghan/Source%20codes.html

The 1Shot-MaxPol library:

Mahdi S. Hosseini and Konstantinos N. Plataniotis 
"Convolutional Deblurring for Natural Imaging," 
IEEE Transactions on Image Processing, 2019.
https://github.com/mahdihosseini/1Shot-MaxPol

The FQPath library:

Hosseini, Mahdi S., Jasper AZ Brawley-Hayes, Yueyang Zhang, Lyndon Chan, Konstantinos N. Plataniotis, and Savvas Damaskinos
"Focus Quality Assessment of High-Throughput Whole Slide Imaging in Digital Pathology." 
IEEE Transactions on Medical Imaging (2019)
https://github.com/mahdihosseini/FQPath

The Fast N-D Grayscale Image Segmentation library:

Fast N-D Grayscale Image Segmenation With c- or Fuzzy c-Means
https://github.com/AntonSemechko/Fast-Fuzzy-C-Means-Segmentation

The Stain Deconvolution library:

SCD_FastICA
https://github.com/lisatostrams/SCD_FastICA

and the Colour Image Normalization library:

Finlayson, G., Schiele, B., & Crowley, J. (1998). 
Comprehensive Colour Image Normalization. 
Computer Vision—ECCV’98, 1406, 475–490. 
https://doi.org/10.1007/BFb0055655
https://it.mathworks.com/matlabcentral/fileexchange/60360-comprehensive-colour-normalization

About

Source code for the 2021 ICASSP paper "Acute Lymphoblastic Leukemia detection based on adaptive unsharpening and Deep Learning"

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages