A Smart Handheld Edge Device for On-Site Diagnosis and Classification of Texture and Stiffness of Excised Colorectal Cancer Polyps
Ozdemir Can KaraJiaqi XueNethra VenkatayogiTarunraj G. MohanrajYuki HirataNaruhiko IkomaS. Farokh AtashzarFarshid Alambeigi
Ozdemir Can KaraJiaqi XueNethra Venkatayogi
...+4
Farshid Alambeigi
Sep 2023
0被引用
0笔记
开学季活动火爆进行中，iPad、蓝牙耳机、拍立得、键盘鼠标套装等你来拿
摘要原文
This paper proposes a smart handheld textural sensing medical device with complementary Machine Learning (ML) algorithms to enable on-site Colorectal Cancer (CRC) polyp diagnosis and pathology of excised tumors. The proposed unique handheld edge device benefits from a unique tactile sensing module and a dual-stage machine learning algorithms (composed of a dilated residual network and a t-SNE engine) for polyp type and stiffness characterization. Solely utilizing the occlusion-free, illumination-resilient textural images captured by the proposed tactile sensor, the framework is able to sensitively and reliably identify the type and stage of CRC polyps by classifying their texture and stiffness, respectively. Moreover, the proposed handheld medical edge device benefits from internet connectivity for enabling remote digital pathology (boosting the diagnosis in operating rooms and promoting accessibility and equity in medical diagnosis).
