30 citations · 92 across the 8 of their papers we have counts for
8 papers
LinGuinE: Longitudinal Guidance Estimation for Volumetric Tumour Segmentation
Nadine Garibli, Mayank Patwari, Bence Csiba +2
Longitudinal volumetric tumour segmentation is critical for radiotherapy planning and response assessment, yet this problem is underexplored and most methods produce single-timepoi…
Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT
Fabian Wagner, Mareike Thies, Felix Denzinger +7
Low-dose computed tomography (CT) denoising algorithms aim to enable reduced patient dose in routine CT acquisitions while maintaining high image quality. Recently, deep learning~(…
Limited Parameter Denoising for Low-dose X-ray Computed Tomography Using Deep Reinforcement Learning
Mayank Patwari, Ralf Gutjahr, Rainer Raupach +1
The use of deep learning has successfully solved several problems in the field of medical imaging. Deep learning has been applied to the CT denoising problem successfully. However,…
A quantitative comparison of plantar soft tissue strainability distribution and homogeneity between ulcerated and non-ulcerated patients using strain elastography
Maaynk Patwari, Panagiotis Chazistergos, Lakshmi Sundar +3
The primary objective of this study was to develop a method that allows accurate quantification of plantar soft tissue stiffness distribution and homogeneity. The secondary aim of…
Ultra Low-Parameter Denoising: Trainable Bilateral Filter Layers in Computed Tomography
Fabian Wagner, Mareike Thies, Mingxuan Gu +9
Computed tomography is widely used as an imaging tool to visualize three-dimensional structures with expressive bone-soft tissue contrast. However, CT resolution and radiation dose…
Low Dose Helical CBCT denoising by using domain filtering with deep reinforcement learning
Wooram Kang, Mayank Patwari
Cone Beam Computed Tomography(CBCT) is a now known method to conduct CT imaging. Especially, The Low Dose CT imaging is one of possible options to protect organs of patients when c…
Low Dose CT Denoising via Joint Bilateral Filtering and Intelligent Parameter Optimization
Mayank Patwari, Ralf Gutjahr, Rainer Raupach +1
Denoising of clinical CT images is an active area for deep learning research. Current clinically approved methods use iterative reconstruction methods to reduce the noise in CT ima…
JBFnet -- Low Dose CT Denoising by Trainable Joint Bilateral Filtering
Mayank Patwari, Ralf Gutjahr, Rainer Raupach +1
Deep neural networks have shown great success in low dose CT denoising. However, most of these deep neural networks have several hundred thousand trainable parameters. This, combin…