Integrating Transformer and Bidirectional Long Short-Term Memory for Intelligent Breast Cancer Detection from Histopathology Biopsy Images  

作　　者：Prasanalakshmi Balaji Omar Alqahtani Sangita Babu Mousmi Ajay Chaurasia Shanmugapriya Prakasam 

机构地区：[1]Department of Computer Science,College of Computer Science,King Khalid University,Abha,61451,Saudi Arabia [2]College of Science and Arts in Rijal Alma,King Khalid University,Abha,61451,Saudi Arabia [3]Department of Information Technology,Muffakham Jah College of Engineering and Technology,Hyderabad,500034,India [4]Department of Computer Science and Business Systems,Rajalakshmi Engineering College,Thandalam,602105,India

出　　处：《Computer Modeling in Engineering & Sciences》2024年第10期443-458,共16页工程与科学中的计算机建模（英文）

基　　金：Deanship of Research and Graduate Studies at King Khalid University for funding this work through Small Group Research Project under Grant Number RGP1/261/45.

摘　　要：Breast cancer is a significant threat to the global population,affecting not only women but also a threat to the entire population.With recent advancements in digital pathology,Eosin and hematoxylin images provide enhanced clarity in examiningmicroscopic features of breast tissues based on their staining properties.Early cancer detection facilitates the quickening of the therapeutic process,thereby increasing survival rates.The analysis made by medical professionals,especially pathologists,is time-consuming and challenging,and there arises a need for automated breast cancer detection systems.The upcoming artificial intelligence platforms,especially deep learning models,play an important role in image diagnosis and prediction.Initially,the histopathology biopsy images are taken from standard data sources.Further,the gathered images are given as input to the Multi-Scale Dilated Vision Transformer,where the essential features are acquired.Subsequently,the features are subjected to the Bidirectional Long Short-Term Memory(Bi-LSTM)for classifying the breast cancer disorder.The efficacy of the model is evaluated using divergent metrics.When compared with other methods,the proposed work reveals that it offers impressive results for detection.

关 键 词：Bidirectional long short-term memory breast cancer detection feature extraction histopathology biopsy images multi-scale dilated vision transformer 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]