72 citations · 185 across the 18 of their papers we have counts for
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Evaluation of Multi-Slice Inputs to Convolutional Neural Networks for Medical Image Segmentation
Minh H. Vu, Guus Grimbergen, Tufve Nyholm +1
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 sin…
TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks
Minh H. Vu, Tufve Nyholm, Tommy Löfstedt
Glioma is one of the most common types of brain tumors; it arises in the glial cells in the human brain and in the spinal cord. In addition to having a high mortality rate, glioma…
End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor Segmentation
Minh H. Vu, Guus Grimbergen, Attila Simkó +2
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…
A Generalized Network for MRI Intensity Normalization
A. Simkó, T. Löfstedt, A. Garpebring +2
Image normalization, the correction for intra-volume inhomogeneities in magnetic resonance imaging (MRI) data has little significance for visual diagnosis, but is a crucial step be…