DETEKSI KANKER PARU-PARU DAN USUS BESAR PADA GAMBAR HISTOPATOLOGI MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK

IDRIS, MAULANA (2024) DETEKSI KANKER PARU-PARU DAN USUS BESAR PADA GAMBAR HISTOPATOLOGI MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK. Undergraduate thesis, UPN VETERAN JAWA TIMUR.

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Abstract

Lung cancer is a serious and fatal condition. It develops when cells in the lungs grow and divide uncontrollably, forming tumors. Early detection is crucial in improving patient survival rates. Additionally, cases of colon cancer are also frequently encountered and are often associated with lung cancer patients due to the significant percentage of both cancers being found in a single patient. Colon cancer is equally as dangerous as lung cancer. In this case study, we developed a program to identify lung and colon cancer using a Convolutional Neural Network (CNN) method to detect histopathological images of lung and colon cancer patients available in the LC25000 Dataset. The LC25000 Dataset contains 25,000 color histopathology image samples of lung and colon tissue, both cancerous and normal. In this study, we used a pre-trained CNN model, Inception-V3, which achieved an accuracy of 99.4% with a total training time of only 2,778 seconds or 47 minutes.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	ANGGRAENY, FETTY TRI	NIDN0711028201	fettyanggraeny.if@upnjatim.ac.id
Thesis advisor	MUMPUNI, RETNO	NIDN0016078703	retnomumpuni.if@upnjatim.ac.id

Subjects:

Q Science > Q Science (General)
Q Science > QA Mathematics > QA76.87 Neural computers
T Technology > T Technology (General)

Divisions:

Faculty of Computer Science > Departemen of Informatics

Depositing User:

Mr Maulana Idris

Date Deposited:

08 Aug 2024 06:39

Last Modified:

08 Aug 2024 06:39

URI:

https://repository.upnjatim.ac.id/id/eprint/28105