Machine Learning Interface for Medical Image Analysis

Machine Learning Applications in Medical Image Analysis

Medical Image Classification by Supervised Machine Learning

In this paper, Support Vector Machine (SVM) was used to learn image feature characteristics for image classification. Several image visual features describe the shape, edge, and texture of image (including histogram, spatial layout, coherence moment and gabor features) have been employed in this paper to categorize the 500 test images into 46 classes. The result shows that the spatial relations...

Machine Learning for Dental Image Analysis

In order to study the application of artificial intelligence (AI) to dental imaging, we applied AI technology to classify a set of panoramic radiographs using (a) a convolutional neural network (CNN) which is a form of an artificial neural network (ANN), (b) representative image cognition algorithms that implement scale-invariant feature transform (SIFT), and (c) histogram of oriented gradients...

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...

A human-machine interface for medical image analysis and visualization in virtual environments

Evaluation of three-dimensional anatomical data, as they are obtained by techniques like Magnetic Resonance Imaging (MRI) or Computed Tomography (CT), is an elaborate and time-consuming process. Though there is remarkable success in accelerating this task by automation [1], it still demands human interaction [2]. Specialists can be supported in this work through modern means of man-machine comm...