Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/458455
Title: Multimodal medical image fusion techniques for the early detection of brain disorders
Researcher: Reena Benjamin J
Guide(s): Jayasree T
Keywords: Medical Image Fusion
Brain Disorders
Neural Networks
University: Anna University
Completed Date: 2021
Abstract: Image fusion is the process of merging significant information from two or more images into a single image so that the fused image is more accurate and informative than any one of the input source images. Image fusion finds its application in different fields such as remote sensing, medical imaging, surveillance, biometrics, military and astronomy. Nowadays, medical imaging plays a vital role in various healthcare applications including diagnosis of diseases, treatment planning etc. Medical image fusion is the process of combining images from different imaging modalities to enhance the image quality and information to increase the clinical applicability of diagnosing diseases and thus go for surgical planning in a short period of time. newlineGenerally, medical imaging modalities carry complementary information of the human organs and tissues which guide the radiologists and doctors to identify the diseases easily. The most complex human organ is the brain. The brain is responsible for our actions, feeling, memory, thought and experience of the world. The various disorders related to the brain are Alzheimer s disease, brain tumour, stroke, motor neuron disease etc. The various brain imaging techniques allow physicians to study brain activity and the problems related to the brain without invasive neurosurgery. Some of them are Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT). CT and MRI are called anatomical images since they provide only structural information. CT images show the information of bone structures, whereas MRI images give details of soft delicate tissues. newline
Pagination: xxv,201p.
URI: http://hdl.handle.net/10603/458455
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File20 kBAdobe PDFView/Open
02_prelim_pages.pdf2.1 MBAdobe PDFView/Open
03_contents.pdf145.76 kBAdobe PDFView/Open
04_abstracts.pdf124.78 kBAdobe PDFView/Open
05_chapter1.pdf741.42 kBAdobe PDFView/Open
06_chapter2.pdf1.07 MBAdobe PDFView/Open
07_chapter3.pdf3.75 MBAdobe PDFView/Open
08_chapter4.pdf1.2 MBAdobe PDFView/Open
09_chapter5.pdf4.89 MBAdobe PDFView/Open
10_chapter6.pdf2.36 MBAdobe PDFView/Open
11_annexures.pdf261.32 kBAdobe PDFView/Open
80_recommendation.pdf128.98 kBAdobe PDFView/Open
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