Machine (Deep) Learning Methods for Image Processing and Radiomics

Radiomics and Deep Learning

Prostate cancer radiomics: A study on IMRT response prediction based on MR image features and machine learning approaches

Introduction: To develop different radiomic models based on radiomic features and machine learning methods to predict early intensity modulated radiation therapy (IMRT) response.   Materials and Methods: Thirty prostate patients were included. All patients underwent pre ad post-IMRT T2 weighted and apparent diffusing coefficient (ADC) magnetic resonance imagi...

Machine Learning in Image Processing

1GREYC, UMR CNRS 6072, ENSICAEN, Université de Caen Basse-Normandie, 6 Boulevard du Maréchal Juin, 14050 Caen cedex, France 2Pattern Recognition and Image Analysis Team, Computer Science Laboratory (LI), Université François Rabelais de Tours, 64 avenue Jean Portalis, 37200 Tours, France 3Models Images Vision (MIV) Team, Image Sciences, Computer Sciences and Remote Sensing Laboratory (LSIIT), Un...

Machine Learning Methods for Automatic Image Colorization

Automatic image colorization consists in adding colors to a new greyscale image without any user intervention. The problem, stated like this, is ill-posed, in the sense that one cannot guess the colors to assign to a greyscale image without any prior knowledge. Indeed, many objects can have different colors: not

Machine learning methods for histopathological image analysis

Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have some issues to be considered. In this mini-review, we introduce the application of digital pathological image analysis using machine learning algorithms, addre...