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# Quantifying imbalanced classification methods for leukemia detection 

This codebase is part of supplementary materials of our paper *"__Quantifying imbalanced classification methods for leukemia detection__"*
***
## Authors: 
Deponker Sarker Depto, Md. Mashfiq Rizvee, Aimon Rahman, Hasib Zunair, M Sohel Rahman and M.R.C. Mahdy

## Short Description: 
Leukemia is a cancer of the body's blood-forming tissues, including the bone marrow and the lymphatic system. There's a good chance of survival if leukemia is detected early. But imbalance is a crucial issue in medical imaging and diagonosis results of leukemia by CAD systems becomes often skewed. Through our effort we have tried to alleviate the imbalance class problem for leukemia detection.


Figure: We have presented classified and misclassified samples and their corresponding superimposed feature maps from best models to input images.

## Published Paper Link
[Quantifying imbalanced classification methods for leukemia detection](https://www.sciencedirect.com/science/article/abs/pii/S0010482522010800)

## Citation
  ```sh
 @article{depto2023quantifying,
  title={Quantifying imbalanced classification methods for leukemia detection},
  author={Depto, Deponker Sarker and Rizvee, Md Mashfiq and Rahman, Aimon and Zunair, Hasib and Rahman, M Sohel and Mahdy, MRC},
  journal={Computers in Biology and Medicine},
  volume={152},
  pages={106372},
  year={2023},
  publisher={Elsevier}
}
  ```

## DOI
https://doi.org/10.1016/j.compbiomed.2022.106372

## Requirments
This work requirs
- Python:     3.8.1
- Tensorflow: 2.3.0
- Keras:      2.4.0

## Imbalance Scanario
We provide bar-chart depiction of imbalanced scanarios







## License
Distributed under the MIT License.

	a/README.md		b/README.md
1	# Quantifying imbalanced classification methods for leukemia detection	1	# Quantifying imbalanced classification methods for leukemia detection
2		2
3	This codebase is part of supplementary materials of our paper "__Quantifying imbalanced classification methods for leukemia detection__"	3	This codebase is part of supplementary materials of our paper "__Quantifying imbalanced classification methods for leukemia detection__"
4	***	4	***
5	## Authors:	5	## Authors:
6	Deponker Sarker Depto, Md. Mashfiq Rizvee, Aimon Rahman, Hasib Zunair, M Sohel Rahman and M.R.C. Mahdy	6	Deponker Sarker Depto, Md. Mashfiq Rizvee, Aimon Rahman, Hasib Zunair, M Sohel Rahman and M.R.C. Mahdy
7		7
8	## Short Description:	8	## Short Description:
9	Leukemia is a cancer of the body's blood-forming tissues, including the bone marrow and the lymphatic system. There's a good chance of survival if leukemia is detected early. But imbalance is a crucial issue in medical imaging and diagonosis results of leukemia by CAD systems becomes often skewed. Through our effort we have tried to alleviate the imbalance class problem for leukemia detection.	9	Leukemia is a cancer of the body's blood-forming tissues, including the bone marrow and the lymphatic system. There's a good chance of survival if leukemia is detected early. But imbalance is a crucial issue in medical imaging and diagonosis results of leukemia by CAD systems becomes often skewed. Through our effort we have tried to alleviate the imbalance class problem for leukemia detection.
10		10
11	<img src="media/New Project.png" width="">
12	Figure: We have presented classified and misclassified samples and their corresponding superimposed feature maps from best models to input images.	11	Figure: We have presented classified and misclassified samples and their corresponding superimposed feature maps from best models to input images.
13		12
14	## Published Paper Link	13	## Published Paper Link
15	[Quantifying imbalanced classification methods for leukemia detection](https://www.sciencedirect.com/science/article/abs/pii/S0010482522010800)	14	[Quantifying imbalanced classification methods for leukemia detection](https://www.sciencedirect.com/science/article/abs/pii/S0010482522010800)
16		15
17	## Citation	16	## Citation
18	```sh	17	```sh
19	@article{depto2023quantifying,	18	@article{depto2023quantifying,
20	title={Quantifying imbalanced classification methods for leukemia detection},	19	title={Quantifying imbalanced classification methods for leukemia detection},
21	author={Depto, Deponker Sarker and Rizvee, Md Mashfiq and Rahman, Aimon and Zunair, Hasib and Rahman, M Sohel and Mahdy, MRC},	20	author={Depto, Deponker Sarker and Rizvee, Md Mashfiq and Rahman, Aimon and Zunair, Hasib and Rahman, M Sohel and Mahdy, MRC},
22	journal={Computers in Biology and Medicine},	21	journal={Computers in Biology and Medicine},
23	volume={152},	22	volume={152},
24	pages={106372},	23	pages={106372},
25	year={2023},	24	year={2023},
26	publisher={Elsevier}	25	publisher={Elsevier}
27	}	26	}
28	```	27	```
29		28
30	## DOI	29	## DOI
31	https://doi.org/10.1016/j.compbiomed.2022.106372	30	https://doi.org/10.1016/j.compbiomed.2022.106372
32		31
33	## Requirments	32	## Requirments
34	This work requirs	33	This work requirs
35	- Python: 3.8.1	34	- Python: 3.8.1
36	- Tensorflow: 2.3.0	35	- Tensorflow: 2.3.0
37	- Keras: 2.4.0	36	- Keras: 2.4.0
38		37
39	## Imbalance Scanario	38	## Imbalance Scanario
40	We provide bar-chart depiction of imbalanced scanarios	39	We provide bar-chart depiction of imbalanced scanarios
41	![Imbalance scanario](media/bar-char-imbl.png)	40
42		41
43
44	## Results
45	We report the best scores from our implemented models
46	![Results of best models](media/results.png)
47
48	## License	42	## License
49	Distributed under the MIT License.	43	Distributed under the MIT License.