A Multi-task Network to Detect Junctions in Retinal Vasculature. - Fatmatülzehra Uslu; Anil Anthony Bharath (MICCAI (2), 2018)

Deep Reinforcement Learning for Subpixel Neural Tracking. - Tianhong Dai; Magda Dubois; Kai Arulkumaran; Jonathan Campbell; Cher Bass; Benjamin Billot; Fatmatülzehra Uslu; Vincenzo De Paola; Claudia Clopath; Anil Anthony Bharath (MIDL, 2019)

An Inception Inspired Deep Network to Analyse Fundus Images. - Fatmatülzehra Uslu (CoRR, 2019)

A recursive Bayesian approach to describe retinal vasculature geometry. - Fatmatülzehra Uslu; Anil Anthony Bharath (Pattern Recognit., 2019)

A Semi-Automatic Method To Segment The Left Atrium in MR Volumes With Varying Slice Numbers. - Fatmatülzehra Uslu; Marta Varela; Anil A. Bharath (EMBC, 2020)

PERI-Net: a parameter efficient residual inception network for medical image segmentation. - Fatmatülzehra Uslu; Cher Bass; Anil A. Bharath (Turkish J. Electr. Eng. Comput. Sci., 2020)

SA-Net: A Sequence Aware Network for the Segmentation of the Left Atrium in Cine MRI Datasets. - Fatmatülzehra Uslu; Marta Varela (ISBI, 2021)

Detecting Aortic Valve Pathology from the 3-Chamber Cine Cardiac MRI View. - Kavitha Vimalesvaran; Fatmatülzehra Uslu; Sameer Zaman; Christoforos Galazis; James Howard; Graham Cole; Anil A. Bharath (MICCAI (1), 2022)

LA-Net: A Multi-Task Deep Network for the Segmentation of the Left Atrium. - Fatmatülzehra Uslu; Marta Varela; Georgia Boniface; Thakshayene Mahenthran; Henry Chubb; Anil A. Bharath (IEEE Trans. Medical Imaging, 2022)

TMS-Net: A segmentation network coupled with a run-time quality control method for robust cardiac image segmentation. - Fatmatülzehra Uslu; Anil A. Bharath (Comput. Biol. Medicine, 2023)

GSM-Net: A global sequence modelling network for the segmentation of short axis CINE MRI images. - Fatmatülzehra Uslu (Comput. Medical Imaging Graph., 2023)

A robust quality estimation method for medical image segmentation with small datasets. - Fatmatülzehra Uslu; Marta Varela (Biomed. Signal Process. Control., 2024)