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.

A deep learning framwork for lung cancer prediction

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

Biorepository application for tracking biospecimens.