A new deep learning model with interface for fine needle aspiration cytology image-based breast cancer detection
Manjula Kalita,
Lipi B. Mahanta,
Anup Kumar Das
et al.
Abstract:Cytological evaluation through microscopic image analysis of fine needle aspiration cytology (FNAC) is pivotal in the initial screening of breast cancer. The sensitivity of FNAC as a screening tool relies on both image quality and the pathologist’s expertise. To enhance diagnostic accuracy and alleviate the pathologist’s workload, a computer-aided diagnosis (CAD) system was developed. A comparative study was conducted, assessing twelve candidate pre-trained models. Utilizing a locally gathered FNAC image datas… Show more
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