Browsing by Author "Ebrahimi, Mehran"
Now showing items 1-12 of 12
-
A coherent point drift algorithm for breast image registration via surface markers
Ahmadian, Ghazaleh (2017-03-01)Breast Magnetic Resonance Imaging (MRI) is a reliable imaging tool for localization and evaluation of lesions prior to breast conserving surgery (BCS). MR images typically will be used to determine the size and location ... -
Comparative analysis of deep learning and graph cut algorithms for cell image segmentation
Reshad, Ghazal (2020-08-01)Image segmentation is a commonly used technique in digital image processing with many applications in the area of computer vision and medical image analysis. The goal of image segmentation is to partition an image into ... -
Computational methods for medical image registration
Mojica, Mia Carmela (2021-04-01)A significant amount of research has been dedicated to the improvement of techniques in the field of medical image analysis. Imaging modalities have been improved and new acquisition methods have been introduced to reveal ... -
Deep learning approach to discontinuity-preserving image registration
Ng, Eric (2020-05-01)Image registration is an indispensable tool in medical image analysis. Traditionally, registration algorithms are aimed at aligning image pairs using regularizers to impose smoothness restrictions on unknown deformation ... -
A deep learning approach to focal cortical dysplasia segmentation in children with medically intractable epilepsy
Aminpour, Azad (2021-08-01)Paediatric epilepsy is one of the most common neurological disorders and has major impact on the cognition and quality of life of children. Focal Cortical Dysplasia (FCD) is one of the most common causes of medically ... -
Generative models for multi-modality image inpainting and resolution enhancement
Abed jooy Divshali, Aref (2022-04-01)Recently, deep learning methods specifically generative adversarial networks (GANs) have been used to rapidly improve a wide range of image enhancement tasks including image inpainting and image resolution enhancement also ... -
Identifying lesions in paediatric epilepsy using morphometric and textural analysis of magnetic resonance images
Kulaseharan, Sancgeetha (2017-12-01)We develop an image processing pipeline on Magnetic Resonance Imaging (MRI) sequences to identify features of Focal Cortical Dysplasia (FCD) in patients with MRIvisible FCD. We aim to use a computer-aided diagnosis system ... -
Image super resolution via non-local normalized graph Laplacian regularization
Falconer, Cory (2019-05-01)Given we live in a digital age where images are regularly being viewed, posted, or utilized, spectators of such images on occasion could prefer a higher resolution perspective. The process of producing a high-resolution ... -
Mathematical methods for 2D-3D cardiac image registration
Ma, Lok Wan Lorraine (2016-12-01)We propose a mathematical formulation aimed at intensity-based slice-to-volume registration, aligning a cross-sectional slice of a 3D volume to a 2D image. The approach is flexible and can accommodate various regularization ... -
Multi-scale local explanation approach for image analysis using model-agnostic explainable artificial intelligence (XAI)
Hajiyan, Hooria (2022-08-01)The recent success of deep neural networks has generated a remarkable growth in Artificial Intelligence (AI) research, and it received much interest over the past few years. However, one of the main challenges for the broad ... -
Single magnetic resonance image super-resolution using generative adversarial network
Rashid, Shawkh Ibne (2022-08-01)Super-Resolution is the process of converting given low-resolution images into corresponding high-resolution ones. The resolution enhancement process applied to medical images can potentially improve diagnostic accuracy ... -
Structure guided image restoration : a deep learning approach
Nazeri Naeini, Kamyar (2019-05-01)Image restoration aims at recovery of degraded images and estimating the original. Over the past few years, computer vision research has been dominated by deep learning techniques in part due to advances in computing ...