29 citations · 34 across the 4 of their papers we have counts for
5 papers
MouseGAN++: Unsupervised Disentanglement and Contrastive Representation for Multiple MRI Modalities Synthesis and Structural Segmentation of Mouse Brain
Ziqi Yu, Xiaoyang Han, Shengjie Zhang +3
Segmenting the fine structure of the mouse brain on magnetic resonance (MR) images is critical for delineating morphological regions, analyzing brain function, and understanding th…
DELAD: Deep Landweber-guided deconvolution with Hessian and sparse prior
Tomas Chobola, Anton Theileis, Jan Taucher +1
We present a model for non-blind image deconvolution that incorporates the classic iterative method into a deep learning application. Instead of using large over-parameterised gene…
Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations
Sophia J. Wagner, Nadieh Khalili, Raghav Sharma +4
In digital pathology, different staining procedures and scanners cause substantial color variations in whole-slide images (WSIs), especially across different laboratories. These co…
Attention based Multiple Instance Learning for Classification of Blood Cell Disorders
Ario Sadafi, Asya Makhro, Anna Bogdanova +4
Red blood cells are highly deformable and present in various shapes. In blood cell disorders, only a subset of all cells is morphologically altered and relevant for the diagnosis.…
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks
Gerda Bortsova, Gijs van Tulder, Florian Dubost +5
Intracranial carotid artery calcification (ICAC) is a major risk factor for stroke, and might contribute to dementia and cognitive decline. Reliance on time-consuming manual annota…