Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks

Tushar Nayak; Niranjana Sampathila; Nitila Gokulkrishnan

doi:10.1109/CONECCT57959.2023.10234757

Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks

Tushar Nayak^*
, Niranjana Sampathila
, Nitila Gokulkrishnan

^*Corresponding author for this work

Manipal Institute of Technology, Manipal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

Lung & Colon cancer are amongst the leading cause of cancer related deaths worldwide. In this study, we used a five-class lung and colon cancer histopathology dataset and applied various image preprocessing techniques such as contrast stretching, unsharp masking, and resizing. We then trained a ResNetl01 model on this preprocessed dataset and achieved a high accuracy of 99.7%. The increased reliability and robustness of deep learning-based histopathology classifiers with high performance computers can enable instantaneous and automated diagnosis which can further help treatment and recovery.

Original language	English
Title of host publication	Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350334395
DOIs	https://doi.org/10.1109/CONECCT57959.2023.10234757
Publication status	Published - 2023
Event	9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023 - Bangalore, India Duration: 14-07-2023 → 16-07-2023

Publication series

Name	Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies

Conference

Conference	9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023
Country/Territory	India
City	Bangalore
Period	14-07-23 → 16-07-23

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Hardware and Architecture
Information Systems
Energy Engineering and Power Technology
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/CONECCT57959.2023.10234757

Cite this

Nayak, T., Sampathila, N., & Gokulkrishnan, N. (2023). Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks. In Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies (Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONECCT57959.2023.10234757

Nayak, Tushar ; Sampathila, Niranjana ; Gokulkrishnan, Nitila. / Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks. Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies).

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title = "Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks",

abstract = "Lung \& Colon cancer are amongst the leading cause of cancer related deaths worldwide. In this study, we used a five-class lung and colon cancer histopathology dataset and applied various image preprocessing techniques such as contrast stretching, unsharp masking, and resizing. We then trained a ResNetl01 model on this preprocessed dataset and achieved a high accuracy of 99.7\%. The increased reliability and robustness of deep learning-based histopathology classifiers with high performance computers can enable instantaneous and automated diagnosis which can further help treatment and recovery.",

author = "Tushar Nayak and Niranjana Sampathila and Nitila Gokulkrishnan",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023 ; Conference date: 14-07-2023 Through 16-07-2023",

year = "2023",

doi = "10.1109/CONECCT57959.2023.10234757",

language = "English",

series = "Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies",

address = "United States",

}

Nayak, T, Sampathila, N & Gokulkrishnan, N 2023, Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks. in Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies. Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies, Institute of Electrical and Electronics Engineers Inc., 9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023, Bangalore, India, 14-07-23. https://doi.org/10.1109/CONECCT57959.2023.10234757

Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks. / Nayak, Tushar; Sampathila, Niranjana; Gokulkrishnan, Nitila.
Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks

AU - Nayak, Tushar

AU - Sampathila, Niranjana

AU - Gokulkrishnan, Nitila

PY - 2023

Y1 - 2023

N2 - Lung & Colon cancer are amongst the leading cause of cancer related deaths worldwide. In this study, we used a five-class lung and colon cancer histopathology dataset and applied various image preprocessing techniques such as contrast stretching, unsharp masking, and resizing. We then trained a ResNetl01 model on this preprocessed dataset and achieved a high accuracy of 99.7%. The increased reliability and robustness of deep learning-based histopathology classifiers with high performance computers can enable instantaneous and automated diagnosis which can further help treatment and recovery.

AB - Lung & Colon cancer are amongst the leading cause of cancer related deaths worldwide. In this study, we used a five-class lung and colon cancer histopathology dataset and applied various image preprocessing techniques such as contrast stretching, unsharp masking, and resizing. We then trained a ResNetl01 model on this preprocessed dataset and achieved a high accuracy of 99.7%. The increased reliability and robustness of deep learning-based histopathology classifiers with high performance computers can enable instantaneous and automated diagnosis which can further help treatment and recovery.

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UR - https://www.scopus.com/pages/publications/85172709795#tab=citedBy

U2 - 10.1109/CONECCT57959.2023.10234757

DO - 10.1109/CONECCT57959.2023.10234757

M3 - Conference contribution

AN - SCOPUS:85172709795

T3 - Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies

BT - Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023

Y2 - 14 July 2023 through 16 July 2023

ER -

Nayak T, Sampathila N, Gokulkrishnan N. Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks. In Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies. Institute of Electrical and Electronics Engineers Inc. 2023. (Proceedings of CONECCT 2023 - 9th International Conference on Electronics, Computing and Communication Technologies). doi: 10.1109/CONECCT57959.2023.10234757

Processing and Detection of Lung and Colon Cancer from Histopathological Images using Deep Residual Networks

Abstract

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