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Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation
Asif Hanif, Muzammal Naseer, Salman Khan +2
It is imperative to ensure the robustness of deep learning models in critical applications such as, healthcare. While recent advances in deep learning have improved the performance…
Learnable Weight Initialization for Volumetric Medical Image Segmentation
Shahina Kunhimon, Abdelrahman Shaker, Muzammal Naseer +2
Hybrid volumetric medical image segmentation models, combining the advantages of local convolution and global attention, have recently received considerable attention. While mainly…
3D Mitochondria Instance Segmentation with Spatio-Temporal Transformers
Omkar Thawakar, Rao Muhammad Anwer, Jorma Laaksonen +3
Accurate 3D mitochondria instance segmentation in electron microscopy (EM) is a challenging problem and serves as a prerequisite to empirically analyze their distributions and morp…
Learning Enriched Features for Fast Image Restoration and Enhancement
Syed Waqas Zamir, Aditya Arora, Salman Khan +4
Given a degraded input image, image restoration aims to recover the missing high-quality image content. Numerous applications demand effective image restoration, e.g., computationa…
Multimodal Multi-Head Convolutional Attention with Various Kernel Sizes for Medical Image Super-Resolution
Mariana-Iuliana Georgescu, Radu Tudor Ionescu, Andreea-Iuliana Miron +4
Super-resolving medical images can help physicians in providing more accurate diagnostics. In many situations, computed tomography (CT) or magnetic resonance imaging (MRI) techniqu…
Transformers in Medical Imaging: A Survey
Fahad Shamshad, Salman Khan, Syed Waqas Zamir +4
Following unprecedented success on the natural language tasks, Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results a…
CyTran: A Cycle-Consistent Transformer with Multi-Level Consistency for Non-Contrast to Contrast CT Translation
Nicolae-Catalin Ristea, Andreea-Iuliana Miron, Olivian Savencu +4
We propose a novel approach to translate unpaired contrast computed tomography (CT) scans to non-contrast CT scans and the other way around. Solving this task has two important app…
CycleISP: Real Image Restoration via Improved Data Synthesis
Syed Waqas Zamir, Aditya Arora, Salman Khan +4
The availability of large-scale datasets has helped unleash the true potential of deep convolutional neural networks (CNNs). However, for the single-image denoising problem, captur…