Cancer classification using deep learning from medical image data

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Bibliografische gegevens
Hoofdauteurs:	Monir, Raiyan Janik, Shaon, Shoeb Islam, Noman, Syed Mohammad, Iqbal, Sahariar
Andere auteurs:	Ashraf, Faisal Bin
Formaat:	Thesis
Taal:	English
Gepubliceerd in:	Brac University 2022
Onderwerpen:	Cancer Deep learning Artificial neural networks (ANN) CNN Cancer detection Medical image data Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Image processing > Digital techniques.
Online toegang:	http://hdl.handle.net/10361/17044

id	10361-17044
record_format	dspace
spelling	10361-170442022-07-31T21:01:34Z Cancer classification using deep learning from medical image data Monir, Raiyan Janik Shaon, Shoeb Islam Noman, Syed Mohammad Iqbal, Sahariar Ashraf, Faisal Bin Department of Computer Science and Engineering, Brac University Cancer Deep learning Artificial neural networks (ANN) CNN Cancer detection Medical image data Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Image processing -- Digital techniques. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (page 37). Cancer is a disease in which some of the body’s cells grow uncontrollably and spread to other parts of the body. Cancer can start almost anywhere in the human body, which is made up of trillions of cells. There is usually no cure for this disease and it is often believed to be untreatable. Breast cancer ranks second among the most fatal cancers, especially in women. Every year many women suffer and die because of breast cancer. Early detection of the disease can save many lives. Breast cancer screening with mammography is essential because it can detect any breast masses or calcifications early on. Because breast tissue is dense, detecting cancer mass is difficult, leading radiologists to use machine learning (ML) techniques and artificial neural networks (ANN) to speed up the detection of cancer. This paper explores the Mini DDSM dataset, containing 9698 digital mammogram images, which were augmented and preprocessed, and fed into CNN and MobileNet Architecture with the aim of detecting normal, benign and cancerous tissues with high accuracy. Therefore, our aim is to apply the deep neural network based algorithm on a cancer image dataset to classify cancer and take advantage of image analysis, pattern recognition, and classification processes, and then validating the image classification outcome against medical specialist expertise. The main objective of this research is to acquire a higher accurate outcome on detecting cancer from medical mammography. Index Terms— Breast cancer detection, neural network, Deep learning, Digital image processing. Raiyan Janik Monir Shoeb Islam Shaon Syed Mohammad Noman Sahariar Iqbal B. Computer Science 2022-07-31T05:09:44Z 2022-07-31T05:09:44Z 2022 2022-01 Thesis ID 19301281 ID 18101138 ID 17301125 ID 18101553 http://hdl.handle.net/10361/17044 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 37 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Cancer Deep learning Artificial neural networks (ANN) CNN Cancer detection Medical image data Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Image processing -- Digital techniques.
spellingShingle	Cancer Deep learning Artificial neural networks (ANN) CNN Cancer detection Medical image data Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Image processing -- Digital techniques. Monir, Raiyan Janik Shaon, Shoeb Islam Noman, Syed Mohammad Iqbal, Sahariar Cancer classification using deep learning from medical image data
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
author2	Ashraf, Faisal Bin
author_facet	Ashraf, Faisal Bin Monir, Raiyan Janik Shaon, Shoeb Islam Noman, Syed Mohammad Iqbal, Sahariar
format	Thesis
author	Monir, Raiyan Janik Shaon, Shoeb Islam Noman, Syed Mohammad Iqbal, Sahariar
author_sort	Monir, Raiyan Janik
title	Cancer classification using deep learning from medical image data
title_short	Cancer classification using deep learning from medical image data
title_full	Cancer classification using deep learning from medical image data
title_fullStr	Cancer classification using deep learning from medical image data
title_full_unstemmed	Cancer classification using deep learning from medical image data
title_sort	cancer classification using deep learning from medical image data
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/17044
work_keys_str_mv	AT monirraiyanjanik cancerclassificationusingdeeplearningfrommedicalimagedata AT shaonshoebislam cancerclassificationusingdeeplearningfrommedicalimagedata AT nomansyedmohammad cancerclassificationusingdeeplearningfrommedicalimagedata AT iqbalsahariar cancerclassificationusingdeeplearningfrommedicalimagedata
_version_	1814307876115578880

Cancer classification using deep learning from medical image data

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