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Full-Text Articles in Radiology
Using Deep Learning To Analyze Materials In Medical Images, Carson Molder
Using Deep Learning To Analyze Materials In Medical Images, Carson Molder
Computer Science and Computer Engineering Undergraduate Honors Theses
Modern deep learning architectures have become increasingly popular in medicine, especially for analyzing medical images. In some medical applications, deep learning image analysis models have been more accurate at predicting medical conditions than experts. Deep learning has also been effective for material analysis on photographs. We aim to leverage deep learning to perform material analysis on medical images. Because material datasets for medicine are scarce, we first introduce a texture dataset generation algorithm that automatically samples desired textures from annotated or unannotated medical images. Second, we use a novel Siamese neural network called D-CNN to predict patch similarity and build …
Sensitivity Of Diffuse Reflectance Spectroscopy To Dose- And Depth-Dependent Changes In Tumor Oxygenation After Radiation Therapy, Daria Semeniak
Sensitivity Of Diffuse Reflectance Spectroscopy To Dose- And Depth-Dependent Changes In Tumor Oxygenation After Radiation Therapy, Daria Semeniak
Graduate Theses and Dissertations
Along with chemotherapy, immunotherapy, and surgery, radiotherapy is one of the most common treatments used against cancer. Around 50% of all cancer patients undergo radiation therapy. While for some patients radiotherapy works efficiently and lead to a complete cancer disappearance, for others treatment outcome may be less favorable due to radioresistance processes happening within a tumor on the molecular level. Radioresistance remains a big challenge for modern oncology. The ability to identify radioresistance at the early stage of radiotherapy would help physicians to improve therapy efficiency. At the current moment, despite the rapid progress in cancer understanding and diagnostic modalities, …