Classification of Breast Invasive Ductal Carcinomas Using Histopathological Images Based on Deep Learning Techniques
- Title
- Classification of Breast Invasive Ductal Carcinomas Using Histopathological Images Based on Deep Learning Techniques
- Creator
- Jaisingh W.; Preethi N.; Murali S.
- Description
- Women suffer from cancer, which is the main reason for death for females around the world. With the use of artificial intelligence, it is possible to predict and detect all types of cancers in the near future. It is not just women who can heal, and most breast cancers are caused by the most vulnerable type of breast. Eighty percent of all diagnoses of carcinoma are invasive ductal carcinomas (IDCs). In this paper, deep learning techniques are extended to support visible semantic evaluation of tumor areas, using convolutional neural networks (CNNs).A CNN is skilled ended a large number of photo covers (tissue areas) after Whole Slide Images (WSI) to study ranked part-based total image. About 600 normal image patches and 200 breast invasive ductal carcinomas are selected for the experiment. It was intended to amount classifier correctness in the detection of IDC tissue areas in Whole Slide Images. We achieved excellent measurable outcomes for an automated finding of IDC areas with our technique. The results are evaluated based on performance measures and compared with a different number of neurons, and the results are highlighted. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Source
- Lecture Notes in Electrical Engineering, Vol-990 LNEE, pp. 261-271.
- Date
- 2023-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Breast cancer; Deep learning; Histology microscopy image; Invasive ductal cancer; Pattern recognition
- Coverage
- Jaisingh W., School of Information Science, Presidency University, Karnataka, Bangalore, 560064, India; Preethi N., Department of Data Science, Christ University, Bengaluru, India; Murali S., Department of Mathematics, Coimbatore Institute of Technology, Coimbatore, 641014, India
- Rights
- Restricted Access
- Relation
- ISSN: 18761100; ISBN: 978-981199089-2
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Jaisingh W.; Preethi N.; Murali S., “Classification of Breast Invasive Ductal Carcinomas Using Histopathological Images Based on Deep Learning Techniques,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/19976.