Patrick M. Jensen
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View article: Integrating MALDI-MSI-Based Spatial Proteomics and Machine Learning to Predict Chemoradiotherapy Outcomes in Head and Neck Cancer
Integrating MALDI-MSI-Based Spatial Proteomics and Machine Learning to Predict Chemoradiotherapy Outcomes in Head and Neck Cancer Open
Head and neck squamous cell carcinoma (HNSCC) is often diagnosed at advanced stages. Due to pronounced intratumoral heterogeneity (ITH), reliable risk stratification and prediction of treatment response remain challenging. This study aimed…
View article: 3D multiscale characterization of the human placenta: Bridging anatomy and histology by X-ray phase-contrast tomography
3D multiscale characterization of the human placenta: Bridging anatomy and histology by X-ray phase-contrast tomography Open
The human placenta exhibits a complex three-dimensional (3D) structure with a interpenetrating vascular tree and large internal interfacial area. In a unique and yet insufficiently explored way, this parenchymal structure enables its multi…
View article: Finding Space-Time Boundaries with Deformable Hypersurfaces
Finding Space-Time Boundaries with Deformable Hypersurfaces Open
Dynamic 3D imaging is increasingly used to study evolving objects. We address the problem of detecting and tracking simple objects that merge or split in time. Common solutions involve detecting topological changes. Instead, we solve the p…
BugNIST -- a Large Volumetric Dataset for Object Detection under Domain Shift Open
Domain shift significantly influences the performance of deep learning algorithms, particularly for object detection within volumetric 3D images. Annotated training data is essential for deep learning-based object detection. However, annot…
Deep Active Latent Surfaces for Medical Geometries Open
Shape priors have long been known to be effective when reconstructing 3D shapes from noisy or incomplete data. When using a deep-learning based shape representation, this often involves learning a latent representation, which can be either…
Review of Serial and Parallel Min-Cut/Max-Flow Algorithms for Computer Vision Open
Minimum cut/maximum flow (min-cut/max-flow) algorithms solve a variety of problems in computer vision and thus significant effort has been put into developing fast min-cut/max-flow algorithms. As a result, it is difficult to choose an idea…
LayeredCNN: Segmenting Layers with Autoregressive Models Open
We address a subclass of segmentation problems where the labels of the image are structured in layers. We propose applying autoregressive CNNs which, when given an image and a partial segmentation of layers, complete the segmentation. Init…
Review of Serial and Parallel Min-Cut/Max-Flow Algorithms for Computer Vision Open
Minimum cut/maximum flow (min-cut/max-flow) algorithms solve a variety of problems in computer vision and thus significant effort has been put into developing fast min-cut/max-flow algorithms. As a result, it is difficult to choose an idea…
3D virtual histopathology of cardiac tissue from Covid-19 patients based on phase-contrast X-ray tomography Open
For the first time, we have used phase-contrast X-ray tomography to characterize the three-dimensional (3d) structure of cardiac tissue from patients who succumbed to Covid-19. By extending conventional histopathological examination by a t…
3D virtual Histopathology of Cardiac Tissue from Covid-19 Patients based on Phase-Contrast X-ray Tomography Open
For the first time, we have used phase-contrast x-ray tomography to characterize the three-dimensional (3d) structure of cardiac tissue from patients who succumbed to Covid-19. By extending conventional histopatholocigal examination by a t…
Min-Cut/Max-Flow Problem Instances for Benchmarking Open
NOTE: This dataset is now outdated. Please see https://doi.org/10.11583/DTU.17091101 for the updated version with many more problems. This is a collection of min-cut/max-flow problem instances that can be used for benchmarking min-cut/max-…
Weakly Supervised Volumetric Image Segmentation with Deformed Templates Open
There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an ap…
Min-Cut/Max-Flow Problem Instances for Benchmarking Open
NOTE: This dataset is now outdated. Please see https://doi.org/10.11583/DTU.17091101 for the updated version with many more problems. This is a collection of min-cut/max-flow problem instances that can be used for benchmarking min-cut/max-…