3 research outputs found
Image Processing for Medical Image Analysis: A Review
Image processing techniques are used widely in medical areas for improving the image in earlier detection and treatment stages, it is very important to discover the abnormality issues in given images, specially in various cancer, tumours such as lung cancer, breast cancer, etc. Image quality and accuracy is the main factors of this work, image quality improvement and assessment are depending on the enhancement stage where pre-processing techniques is used. The principal objectives of this course are to provide basic introduction and techniques for medical image processing and to promote for further study and research in medical image processing
ANALISIS PERFORMA ALGORITMA NAIVE BAYES PADA DETEKSI OTOMATIS CITRA MRI
The brain in humans becomes part of the central nervous system of the human body. The use of imaging with MRI is one that can be used as a first step to detect parts of the human brain. The imaging step is the first step in diagnosing brain tumor. By performing feature extraction, which aims to process the classification of brain tumors, between normal and abnormal brain images using the naive Bayes method. Obtained 41 images which then became 39 datasets. Feature extraction results with 2 classes, normal as many as 20 data and abnormal data 19. The calculation results obtained the value of the normal class of 0.513 and the abnormal class of 0.487 the value of the calculation accuracy of 84.17%
Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques
This paper describes a novel framework for automatic
segmentation of primary tumors and its boundary from brain
MRIs using morphological filtering techniques. This method uses
T2 weighted and T1 FLAIR images. This approach is very
simple, more accurate and less time consuming than existing
methods. This method is tested by fifty patients of different
tumor types, shapes, image intensities, sizes and produced better
results. The results were validated with ground truth images by
the radiologist. Segmentation of the tumor and boundary
detection is important because it can be used for surgical
planning, treatment planning, textural analysis, 3-Dimensional
modeling and volumetric analysisCochin University of Science and Technology2012 5th International Conference on BioMedical Engineering and Informatics (BMEI 2012