Fraunhofer Center for Assistive Information and Communication Solutions – AICOSDescription:
The CLARE project is focused on developing a computer-aided diagnosis support system for cervical cancer screening through the association of a 3D-printed portable microscope with an AI-powered smartphone application that analyses the images acquired from the cytology samples. This project will contribute to the artificial intelligence component of the CLARE system, through the implementation and optimization of a hybrid pipeline for the identification and stratification of abnormal cell regions, combining state of the art deep learning (DL) approaches and conventional machine learning (ML) models.
Outcome:
This dissertation will contribute to the artificial intelligence component of the CLARE system, through the implementation and optimization of a hybrid pipeline for the identification and stratification of abnormal cell regions, combining state of the art deep learning (DL) approaches and conventional machine learning (ML) models.
Expected direct impact in task execution of current and future Computer Vision projects, such as CLARE and TAMI.
Author: Eduardo Silva
Type: MSc thesis
Partner: FEUP – Faculdade de Engenharia da Universidade do Porto
Year: 2021