A supervised learning model for live cell segmentation. - Can Fahrettin Koyuncu; Irem Durmaz; Rengül Çetin-Atalay; Cigdem Gunduz Demir (SIU, 2014)

Dynamic Programming for the Segmentation of Bone Marrow Cells. - Sebastian Krappe; Christian Münzenmayer; Amrei Evert; Can Fahrettin Koyuncu; A. Enis Çetin; Torsten Haferlach; Thomas Wittenberg; Christian Held (Bildverarbeitung für die Medizin, 2015)

Two-Tier Tissue Decomposition for Histopathological Image Representation and Classification. - Tunç Gültekin; Can Fahrettin Koyuncu; Cenk Sokmensuer; Cigdem Gunduz Demir (IEEE Trans. Medical Imaging, 2015)

Automated cell analysis in microscopy images (Mikroskopi görüntülerinde otomatik hücre analizi) - Can Fahrettin Koyuncu (2018)

DeepDistance: A Multi-task Deep Regression Model for Cell Detection in Inverted Microscopy Images. - Can Fahrettin Koyuncu; Gozde Nur Gunesli; Rengül Çetin-Atalay; Cigdem Gunduz Demir (CoRR, 2019)

Three-dimensional histo-morphometric features from light sheet microscopy images result in improved discrimination of benign from malignant glands in prostate cancer. - Can Fahrettin Koyuncu; Andrew Janowczyk; Cheng Lu 001; Patrick Leo; Mehdi Alilou; Adam K. Glaser; Nicholas P. Reder; Jonathan T. C. Liu; Anant Madabhushi (Digital Pathology, 2020)

DeepDistance: A multi-task deep regression model for cell detection in inverted microscopy images. - Can Fahrettin Koyuncu; Gozde Nur Gunesli; Rengül Çetin-Atalay; Cigdem Gunduz Demir (Medical Image Anal., 2020)

Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. - Cheng Lu 001; Can Koyuncu 001; Germán Corredor; Prateek Prasanna; Patrick Leo; Xiangxue Wang; Andrew Janowczyk; Kaustav Bera; James S. Lewis Jr.; Vamsidhar Velcheti; Anant Madabhushi (Medical Image Anal., 2021)

Spatial connectivity of tumor and associated cells (SpaCell): a novel computational pathology biomarker. - Germán Corredor; Can Koyuncu 001; Andrew Janowczyk; Paula Toro; Sepideh Azarianpour; James S. Lewis Jr.; Anant Madabhushi (Digital and Computational Pathology, 2023)

Transformer as a spatially-aware multi-instance learning framework to predict the risk of death for early-stage non-small cell lung cancer. - Yufei Zhou; Can Koyuncu 001; Cristian Barrera; Germán Corredor; Xiangxue Wang; Cheng Lu 001; Anant Madabhushi (Digital and Computational Pathology, 2023)

Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer. - Yufei Zhou; Can Koyuncu 001; Cheng Lu 001; Rainer Grobholz; Ian Katz; Anant Madabhushi; Andrew Janowczyk (Medical Image Anal., 2023)

Measuring dense false positive regions from segmentation result for whole slide tissue histology image. - Zhao Wang; Qianyu Feng; Germán Corredor; Can Koyuncu 001; Cheng Lu 001 (J. Vis. Commun. Image Represent., 2023)

A Guided-Ensembling Approach for Cell Counting in Fluorescence Microscopy Images. - Cengiz Emre Dedeagac; Can Koyuncu 001; Michelle M. Adams; Çagatay Edemen; Berk C. Ugurdag; N. Ilgim Ardic-Avci; H. Fatih Ugurdag (IEEE Access, 2024)

Leveraging weak supervision for cell localization in digital pathology using multitask learning and consistency loss. - Berke Levent Cesur; Ayse Humeyra Dur Karasayar; Pinar Bulutay; Nilgun Kapucuoglu; Cisel Aydin Mericoz; Handan Eren; Omer Faruk Dilbaz; Javidan Osmanli; Burhan Soner Yetkili; Ibrahim Kulac; Can Fahrettin Koyuncu; Cigdem Gunduz Demir (Comput. Biol. Medicine, 2025)