An Automated Detection Process to Detect Ovarian Tissues Using Type P63 Digitized Color Images. - T. M. Shahriar Sazzad; Leisa J. Armstrong; Amiya Kumar Tripathy (ICTAI, 2015)

Type P63 Digitized Color Images Performs Better Identification than Other Stains for Ovarian Tissue Analysis. - T. M. Shahriar Sazzad; Leisa J. Armstrong; Amiya Kumar Tripathy (AMDO, 2016)

An automated approach to detect human ovarian tissues using type P63 counter stained histopathology digitized color images. - T. M. Shahriar Sazzad; Leisa J. Armstrong; Amiya Kumar Tripathy (BHI, 2016)

Type P63 digitized color images performs better identification for ovarian reproductive tissue analysis. - T. M. Shahriar Sazzad; Leisa J. Armstrong; Amiya Kumar Tripathy (IPAS, 2016)

Type P63 Non-counter Stained Digitized Color Images Performs Better Identification than Other Stains for Ovarian Tissue Analysis. - T. M. Shahriar Sazzad; Leisa J. Armstrong; Amiya Kumar Tripathy (IV, 2016)

A Comprehensive Analysis: Automated Ovarian Tissue Detection Using Type P63 Pathology Color Images. - T. M. Shahriar Sazzad; Leisa J. Armstrong; Amiya Kumar Tripathy (MLDM, 2016)

Type P63 Digitized Color Images Performs Better Identification for Ovarian Tissue Analysis. - T. M. Shahriar Sazzad; Leisa J. Armstrong; Amiya Kumar Tripathy (Trans. Mass Data Anal. Images Signals, 2016)

A Framework to Figure Out Breast Cancer Cells Using Ultrasound Images. - Babe Sultana; Farzana Rahman; Hasib Ahmed Nesar; T. M. Shahriar Sazzad (ICCCNT, 2020)

VGG-SCNet: A VGG Net-Based Deep Learning Framework for Brain Tumor Detection on MRI Images. - Mohammad Shahjahan Majib; Md. Mahbubur Rahman; T. M. Shahriar Sazzad; Nafiz Imtiaz Khan; Samrat Kumar Dey (IEEE Access, 2021)