Medical Imaging

Generalizing multistain immunohistochemistry tissue segmentation using one-shot color deconvolution deep neural networks

Generating highly realistic images of skin lesions with GANs

As many other machine learning driven medical image analysis tasks, skin image analysis suffers from a chronic lack of labeled data and skewed class distributions, which poses problems for the training of robust and well-generalizing models. The …

Intraoperative stent segmentation in X-ray fluoroscopy for endovascular aortic repair

Multiple device segmentation for fluoroscopic imaging using multi-task learning

Weakly-supervised localization and classification of proximal femur fractures

Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Semi-supervised deep learning for fully convolutional networks

Deep learning usually requires large amounts of labeled training data, but annotating data is costly and tedious. The framework of semi-supervised learning provides the means to use both labeled data and arbitrary amounts of unlabeled data for …

X-ray in-depth decomposition: Revealing the latent structures

X-ray is the most readily available imaging modality and has a broad range of applications that spans from diagnosis to intra-operative guidance in cardiac, orthopedics, and trauma procedures. Proper interpretation of the hidden and obscured anatomy …