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7 papers · 2 filters
Differential diagnosis and molecular stratification of gastrointestinal stromal tumors on CT images using a radiomics approach
Martijn P. A. Starmans, Milea J. M. Timbergen, Melissa Vos +10
Distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and GISTs molecular analysis is necessary for treatment planning, but challenging due to it…
autoTICI: Automatic Brain Tissue Reperfusion Scoring on 2D DSA Images of Acute Ischemic Stroke Patients
Ruisheng Su, Sandra A. P. Cornelissen, Matthijs van der Sluijs +8
The Thrombolysis in Cerebral Infarction (TICI) score is an important metric for reperfusion therapy assessment in acute ischemic stroke. It is commonly used as a technical outcome…
DS6, Deformation-aware Semi-supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data
Soumick Chatterjee, Kartik Prabhu, Mahantesh Pattadkal +7
Blood vessels of the brain provide the human brain with the required nutrients and oxygen. As a vulnerable part of the cerebral blood supply, pathology of small vessels can cause s…
Spectral Data Augmentation Techniques to quantify Lung Pathology from CT-images
Subhradeep Kayal, Florian Dubost, Harm A. W. M. Tiddens +1
Data augmentation is of paramount importance in biomedical image processing tasks, characterized by inadequate amounts of labelled data, to best use all of the data that is present…
Automated Detection of Cribriform Growth Patterns in Prostate Histology Images
Pierre Ambrosini, Eva Hollemans, Charlotte F. Kweldam +3
Cribriform growth patterns in prostate carcinoma are associated with poor prognosis. We aimed to introduce a deep learning method to detect such patterns automatically. To do so, c…
2.75D: Boosting learning by representing 3D Medical imaging to 2D features for small data
Xin Wang, Ruisheng Su, Weiyi Xie +5
In medical-data driven learning, 3D convolutional neural networks (CNNs) have started to show superior performance to 2D CNNs in numerous deep learning tasks, proving the added val…