602 citations · 816 across the 24 of their papers we have counts for
15 papers · 1 filter
Self-Consistent Recursive Diffusion Bridge for Medical Image Translation
Fuat Arslan, Bilal Kabas, Onat Dalmaz +2
Denoising diffusion models (DDM) have gained recent traction in medical image translation given improved training stability over adversarial models. DDMs learn a multi-step denoisi…
I2I-Mamba: Multi-modal medical image synthesis via selective state space modeling
Omer F. Atli, Bilal Kabas, Fuat Arslan +4
Multi-modal medical image synthesis involves nonlinear transformation of tissue signals between source and target modalities, where tissues exhibit contextual interactions across d…
Self-Supervised MRI Reconstruction with Unrolled Diffusion Models
Yilmaz Korkmaz, Tolga Cukur, Vishal M. Patel
Magnetic Resonance Imaging (MRI) produces excellent soft tissue contrast, albeit it is an inherently slow imaging modality. Promising deep learning methods have recently been propo…
FD-Net: An Unsupervised Deep Forward-Distortion Model for Susceptibility Artifact Correction in EPI
Abdallah Zaid Alkilani, Tolga Çukur, Emine Ulku Saritas
Recent learning-based correction approaches in EPI estimate a displacement field, unwarp the reversed-PE image pair with the estimated field, and average the unwarped pair to yield…
JointNET: A Deep Model for Predicting Active Sacroiliitis from Sacroiliac Joint Radiography
Sevcan Turk, Ahmet Demirkaya, M Yigit Turali +9
Purpose: To develop a deep learning model that predicts active inflammation from sacroiliac joint radiographs and to compare the success with radiologists. Materials and Methods: A…
Content-Based Medical Image Retrieval with Opponent Class Adaptive Margin Loss
Şaban Öztürk, Emin Celik, Tolga Cukur
Broadspread use of medical imaging devices with digital storage has paved the way for curation of substantial data repositories. Fast access to image samples with similar appearanc…
Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
Saban Ozturk, Tolga Cukur
Melanoma is a fatal skin cancer that is curable and has dramatically increasing survival rate when diagnosed at early stages. Learning-based methods hold significant promise for th…
ResViT: Residual vision transformers for multi-modal medical image synthesis
Onat Dalmaz, Mahmut Yurt, Tolga Çukur
Generative adversarial models with convolutional neural network (CNN) backbones have recently been established as state-of-the-art in numerous medical image synthesis tasks. Howeve…
Constrained Ellipse Fitting for Efficient Parameter Mapping with Phase-cycled bSSFP MRI
Kübra Keskin, Uğur Yılmaz, Tolga Çukur
Balanced steady-state free precession (bSSFP) imaging enables high scan efficiency in MRI, but differs from conventional sequences in terms of elevated sensitivity to main field in…
Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformers
Yilmaz Korkmaz, Salman UH Dar, Mahmut Yurt +2
Supervised reconstruction models are characteristically trained on matched pairs of undersampled and fully-sampled data to capture an MRI prior, along with supervision regarding th…
Three Dimensional MR Image Synthesis with Progressive Generative Adversarial Networks
Muzaffer Özbey, Mahmut Yurt, Salman Ul Hassan Dar +1
Mainstream deep models for three-dimensional MRI synthesis are either cross-sectional or volumetric depending on the input. Cross-sectional models can decrease the model complexity…
mustGAN: Multi-Stream Generative Adversarial Networks for MR Image Synthesis
Mahmut Yurt, Salman Ul Hassan Dar, Aykut Erdem +2
Multi-contrast MRI protocols increase the level of morphological information available for diagnosis. Yet, the number and quality of contrasts is limited in practice by various fac…
Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI
Thomas Sanchez, Baran Gözcü, Ruud B. van Heeswijk +4
Compressed sensing applied to magnetic resonance imaging (MRI) allows to reduce the scanning time by enabling images to be reconstructed from highly undersampled data. In this pape…
Learning-Based Compressive MRI
Baran Gözcü, Rabeeh Karimi Mahabadi, Yen-Huan Li +4
In the area of magnetic resonance imaging (MRI), an extensive range of non-linear reconstruction algorithms have been proposed that can be used with general Fourier subsampling pat…
Statistically Segregated k-Space Sampling for Accelerating Multiple-Acquisition MRI
L Kerem Senel, Toygan Kilic, Alper Gungor +5
A central limitation of multiple-acquisition magnetic resonance imaging (MRI) is the degradation in scan efficiency as the number of distinct datasets grows. Sparse recovery techni…