Wufan Chen

TL;DR: Qualitative and quantitative evaluations on a large set of abdominal and mediastinum CT images are carried out and the results show that the proposed ASDL method can be efficiently applied in most current CT systems.

TL;DR: Experimental results show that the present PWLS-TGV method can achieve images with several noticeable gains over the original TV-based method in terms of accuracy and resolution properties.

TL;DR: For low-dose CT image restoration, the presented ndiNLM method is robust in preserving the spatial resolution and identifying the low-contrast structure and may be useful for some clinical applications such as in perfusion imaging, radiotherapy, tumor surveillance, etc.

TL;DR: This work proposes a novel automatic tumor segmentation method for MRI images that treats tumor segmentsation as a classification problem and considers the data distribution of different classes by learning a softmax regression model, which can further improve classification performance.

TL;DR: This paper proposes a novel feature extraction framework for retrieving brain tumors in T1-weighted contrast-enhanced MRI images and demonstrates the power of the proposed algorithm against some related state-of-the-art methods on the same dataset.