SIMPLI is a highly configurable pipeline for the analysis of multiplexed imaging data.

Preprocessing module for large histological images

"Octopus Realtime Encephalography Lab" is the (hard) real-time networked EEG-lab framework I have developed during my PhD Thesis at Brain Research Lab of Hacettepe University Faculty of Medicine Biophysics Lab. It is meant to be a holistic golden-standard solution for all tasks of cortical source localization/networking, brain-computer interface…

UC1 for PROCESS-project. The use case tackles cancer detection and tissue classification on the latest challenges in cancer research using histopathology images, such as CAMELYON and TUPAC.

Two-Tier Tissue Decomposition for Histopathological Image Representation and Classification

MR-TIM: MR-based head tissue modelling

Quantitatively evaluate tumor stroma reaction within ovarian cancers, and establish assocaitaions to prognosis, molecular signatures.

A Deep Learning project to classify whether a tumor in tissues is 'Malignant' or 'Benign'. This project aims at incorporating AI in detecting cancer at premature stages helping doctors save more lives.

Originally developed for scientific outreach presentation at the SFBD-JSDB Conference 2022 held at Strasbourg.

A deep learning framwork for lung cancer prediction

Biorepository application for tracking biospecimens.