activity
20182022
most citedSemi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

19 citations · 53 across the 6 of their papers we have counts for

collaborators

7 papers

eess.IV2022

Multi-Contrast MRI Segmentation Trained on Synthetic Images

Ismail Irmakci, Zeki Emre Unel, Nazli Ikizler-Cinbis +1

In our comprehensive experiments and evaluations, we show that it is possible to generate multiple contrast (even all synthetically) and use synthetically generated images to train…

cs.CV2022★ 14 cited

Neural Transformers for Intraductal Papillary Mucosal Neoplasms (IPMN) Classification in MRI images

Federica Proietto Salanitri, Giovanni Bellitto, Simone Palazzo +9

Early detection of precancerous cysts or neoplasms, i.e., Intraductal Papillary Mucosal Neoplasms (IPMN), in pancreas is a challenging and complex task, and it may lead to a more f…

eess.IV2021★ 19 cited

Hierarchical 3D Feature Learning for Pancreas Segmentation

Federica Proietto Salanitri, Giovanni Bellitto, Ismail Irmakci +3

We propose a novel 3D fully convolutional deep network for automated pancreas segmentation from both MRI and CT scans. More specifically, the proposed model consists of a 3D encode…

eess.IV2021

Information Bottleneck Attribution for Visual Explanations of Diagnosis and Prognosis

Ugur Demir, Ismail Irmakci, Elif Keles +7

Visual explanation methods have an important role in the prognosis of the patients where the annotated data is limited or unavailable. There have been several attempts to use gradi…

eess.IV2020★ 19 cited

Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Syed Muhammad Anwar, Ismail Irmakci, Drew A. Torigian +5

Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful for clinical and rese…

eess.IV2020

Deep Learning for Musculoskeletal Image Analysis

Ismail Irmakci, Syed Muhammad Anwar, Drew A. Torigian +1

The diagnosis, prognosis, and treatment of patients with musculoskeletal (MSK) disorders require radiology imaging (using computed tomography, magnetic resonance imaging(MRI), and…

cs.CV2018★ 1 cited

A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation

Ismail Irmakci, Sarfaraz Hussein, Aydogan Savran +7

Magnetic resonance imaging (MRI) is the non-invasive modality of choice for body tissue composition analysis due to its excellent soft tissue contrast and lack of ionizing radiatio…