Martin Welk
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View article: What are you looking at? Modality contribution in multimodal medical deep learning
What are you looking at? Modality contribution in multimodal medical deep learning Open
View article: Matrix-Valued LogSumExp Approximation for Colour Morphology
Matrix-Valued LogSumExp Approximation for Colour Morphology Open
Mathematical morphology is a part of image processing that employs a moving window to modify pixel values through the application of specific operations. The supremum and infimum are pivotal concepts, yet defining them in a general sense f…
View article: XSRD-Net: EXplainable Stroke Relapse Detection
XSRD-Net: EXplainable Stroke Relapse Detection Open
Stroke is the second most frequent cause of death world wide with an annual mortality of around 5.5 million. Recurrence rates of stroke are between 5 and 25% in the first year. As mortality rates for relapses are extraordinarily high (40%)…
View article: Multimodal Medical Disease Classification with LLaMA II
Multimodal Medical Disease Classification with LLaMA II Open
Medical patient data is always multimodal. Images, text, age, gender, histopathological data are only few examples for different modalities in this context. Processing and integrating this multimodal data with deep learning based methods i…
View article: Head and Neck Tumor Segmentation on MRIs with Fast and Resource-Efficient Staged nnU-Nets
Head and Neck Tumor Segmentation on MRIs with Fast and Resource-Efficient Staged nnU-Nets Open
MRI-guided radiotherapy (RT) planning offers key advantages over conventional CT-based methods, including superior soft tissue contrast and the potential for daily adaptive RT due to the reduction of the radiation burden. In the Head and N…
View article: Matrix-Valued LogSumExp Approximation for Colour Morphology
Matrix-Valued LogSumExp Approximation for Colour Morphology Open
Mathematical morphology is a part of image processing that uses a window that moves across the image to change certain pixels according to certain operations. The concepts of supremum and infimum play a crucial role here, but it proves cha…
View article: An Approach to Colour Morphological Supremum Formation using the LogSumExp Approximation
An Approach to Colour Morphological Supremum Formation using the LogSumExp Approximation Open
Mathematical morphology is a part of image processing that has proven to be fruitful for numerous applications. Two main operations in mathematical morphology are dilation and erosion. These are based on the construction of a supremum or i…
View article: Tackling the class imbalance problem of deep learning-based head and neck organ segmentation
Tackling the class imbalance problem of deep learning-based head and neck organ segmentation Open
Purpose The segmentation of organs at risk (OAR) is a required precondition for the cancer treatment with image- guided radiation therapy. The automation of the segmentation task is therefore of high clinical relevance. Deep learning (DL)-…
View article: Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation
Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation Open
The segmentation of organs at risk (OAR) is a required precondition for the cancer treatment with image guided radiation therapy. The automation of the segmentation task is therefore of high clinical relevance. Deep Learning (DL) based med…
View article: PDE Evolutions for M-Smoothers in One, Two, and Three Dimensions
PDE Evolutions for M-Smoothers in One, Two, and Three Dimensions Open
View article: Stable Backward Diffusion Models that Minimise Convex Energies
Stable Backward Diffusion Models that Minimise Convex Energies Open
View article: Proceedings of the OAGM Workshop 2018
Proceedings of the OAGM Workshop 2018 Open
View article: Superresolution Alignment with Innocence Assumption: Towards a Fair Quality Measurement for Blind Deconvolution
Superresolution Alignment with Innocence Assumption: Towards a Fair Quality Measurement for Blind Deconvolution Open
National audience Quantitative measurements of restoration quality in blind deconvolution are complicated by the necessity to compensate for opposite shifts of reconstructed image and point-spread function. Alignment procedures mentioned f…
View article: Multivariate Medians for Image and Shape Analysis
Multivariate Medians for Image and Shape Analysis Open
Having been studied since long by statisticians, multivariate median concepts found their way into the image processing literature in the course of the last decades, being used to construct robust and efficient denoising filters for multiv…
View article: Multivariate Medians for Image and Shape Analysis
Multivariate Medians for Image and Shape Analysis Open
Having been studied since long by statisticians, multivariate medianconcepts found their way into the image processing literature in thecourse of the last decades, being used to construct robust and efficientdenoising filters for multivari…
View article: Graph Entropies in Texture Segmentation of Images
Graph Entropies in Texture Segmentation of Images Open
We study the applicability of a set of texture descriptors introduced in\nrecent work by the author to texture-based segmentation of images. The texture\ndescriptors under investigation result from applying graph indices from\nquantitative…
View article: Quantile Filtering of Colour Images viaSymmetric Matrices
Quantile Filtering of Colour Images viaSymmetric Matrices Open
Quantile filters, or rank-order filters, are local image filters which assign quantiles of intensities of the input image within neighbourhoods as output image values. Combining a multivariate quantile definition developed in matrix-valued…
View article: Amoeba Techniques for Shape and Texture Analysis
Amoeba Techniques for Shape and Texture Analysis Open
View article: A robust variational model for positive image deconvolution
A robust variational model for positive image deconvolution Open