Guus Grimbergen's research while affiliated with Eindhoven University of Technology and other places
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Publications (5)
Purpose:
When using convolutional neural networks (CNNs) for segmentation of organs and lesions in medical images, the conventional approach is to work with inputs and outputs either as single slice [two-dimensional (2D)] or whole volumes [three-dimensional (3D)]. One common alternative, in this study denoted as pseudo-3D, is to use a stack of adj...
When using Convolutional Neural Networks (CNNs) for segmentation of organs and lesions in medical images, the conventional approach is to work with inputs and outputs either as single slice (2D) or whole volumes (3D). One common alternative, in this study denoted as pseudo-3D, is to use a stack of adjacent slices as input and produce a prediction f...
Kidney tumor segmentation emerges as a new frontier of computer vision in medical imaging. This is partly due to its challenging manual annotation and great medical impact. Within the scope of the Kidney Tumor Segmentation Challenge 2019, that is aiming at combined kidney and tumor segmentation, this work proposes a novel combination of 3D U-Nets--...
Kidney tumor segmentation emerges as a new frontier of computer vision in medical imaging. This is partly due to its challenging manual annotation and great medical impact. Within the scope of the Kits19, that is aiming at combined kidney and tumor segmentation, this work proposes a novel combination of 3D U-Nets---collectively denoted TuNet---util...
Citations
... The x i is the i-th element of X (in any order), and N is the number of pixels or voxels in the images. We employed the soft Sørensen-Dice coefficient (DSC) loss in the segmentation tasks [13,55,56,57,58], defined as, ...
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... These patch designs included extra spatial information and were used to train two separate networks with cascading outputs. Cascaded network architectures were used by Yang et al. [54], Vu et al. [136], Lv et al. [137] , Mu et al. [19], and Wei et al. [64] to discriminate between kidney cancers. The difference between the two methods is that Yang et al. [54] used a Gaussian pyramid to expand the receptive field in the first stage's network structure, while Vu et al. [136] increased the number of layers in the cascade network to three, with the first layer obtaining the results directly, the second layer obtaining the tumor and kidney regions, the third layer obtaining the tumor segmentation results using the input of the second layer cascade, and the fourth layer cascading the final results. ...
