Medical Image Analysis

By A. Dhawan. 2003

640 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation (2019, methodology): “The use of medical imaging technologies such as Magnetic Resonance Imaging (MRI) has rapidly expanded over the last decades, sparking development of dedicated digital image analysis techniques tailored to these often large imaging datasets (3 and even higher dimensional) (Dhawan, 2011).”
Denoising of diffusion MRI using random matrix theory (2016, background): “Redundancy in data is commonly pursued by a local or non-local selection of image patches, a non-trivial and time-consuming approach, especially in case of spatially varying noise (Deledalle et al., 2011; Manjón et al., 2015).”
Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss (2018, methodology): “We validated our proposed unsupervised cross-modality domain adaptation method for biomedical image segmentations on the public dataset of MICCAI 2017 Multi-Modality Whole Heart Segmentation [Zhuang and Shen, 2016].”