Medical Image Classification by Supervised Machine Learning
نویسندگان
چکیده
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 relationship of pixels is a very important feature in medical image data, because medical image data always have similar anatomic regions (lung, liver, head, and so on). Key-words: Medical Image Classification; Support Vector Machine;
منابع مشابه
Automatic road crack detection and classification using image processing techniques, machine learning and integrated models in urban areas: A novel image binarization technique
The quality of the road pavement has always been one of the major concerns for governments around the world. Cracks in the asphalt are one of the most common road tensions that generally threaten the safety of roads and highways. In recent years, automated inspection methods such as image and video processing have been considered due to the high cost and error of manual metho...
متن کاملSemi-supervised Learning for Multi-label Classification
In this report we consider the semi-supervised learning problem for multi-label image classification, aiming at effectively taking advantage of both labeled and unlabeled training data in the training process. In particular, we implement and analyze various semi-supervised learning approaches including a support vector machine (SVM) method facilitated by principal component analysis (PCA), and ...
متن کاملExploratory analysis of using supervised machine learning in [18F] FDG PET/CT images to predict treatment response in patients with metastatic and recurrent Brest tumors
Aim: Despite grate progress in treatments, breast cancer is still the most common invasive cancer and the most cause of cancer related death in women. Treatment could be improved and perhaps standardized if more reliable markers for tumour progression and poor prognosis could be developed. The aim of this study was to evaluate whether patient-based machine learning (ML) driven ...
متن کاملImage Classification using SOM and SVM Feature Extraction
Support Vector Machines (SVMs) are a relatively new supervised classification technique to the land cover mapping community.SVM are machine learning techniques that are used for segmentation and classification of medical pictures, as well as segmentation of white matter hyperintensities (WMH). Although there are various techniques implemented for the classification of image, here combinatorial ...
متن کاملA New Formulation for Cost-Sensitive Two Group Support Vector Machine with Multiple Error Rate
Support vector machine (SVM) is a popular classification technique which classifies data using a max-margin separator hyperplane. The normal vector and bias of the mentioned hyperplane is determined by solving a quadratic model implies that SVM training confronts by an optimization problem. Among of the extensions of SVM, cost-sensitive scheme refers to a model with multiple costs which conside...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006