Comparative Analysis and Fusion of MRI and PET Images based on Wavelets for Clinical Diagnosis

• Autorzy: Sebastian Jinu , King Gnana

Identyfikatory

DOI

10.24425/ijet.2022.143896

• Języki publikacji: EN

Abstrakty

EN

Nowadays, Medical imaging modalities like Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Single Photon Emission Tomography (SPECT), and Computed Tomography (CT) play a crucial role in clinical diagnosis and treatment planning. The images obtained from each of these modalities contain complementary information of the organ imaged. Image fusion algorithms are employed to bring all of this disparate information together into a single image, allowing doctors to diagnose disorders quickly. This paper proposes a novel technique for the fusion of MRI and PET images based on YUV color space and wavelet transform. Quality assessment based on entropy showed that the method can achieve promising results for medical image fusion. The paper has done a comparative analysis of the fusion of MRI and PET images using different wavelet families at various decomposition levels for the detection of brain tumors as well as Alzheimer’s disease. The quality assessment and visual analysis showed that the Dmey wavelet at decomposition level 3 is optimum for the fusion of MRI and PET images. This paper also compared the results of several fusion rules such as average, maximum, and minimum, finding that the maximum fusion rule outperformed the other two.

Słowa kluczowe

EN

MRI; PET; multimodality medical image fusion; wavelet transform; brain tumor; Alzheimer’s disease; YUV color space

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2022
• Tom: Vol. 68. No. 4
• Strony: 867--873
• Opis fizyczny: Bibliogr. 25 poz., fot., rys., tab., wykr.

Twórcy

autor

Sebastian Jinu

• Sahrdaya College of Engineering and Technology, Thrissur, Kerala, India under APJ Abdul Kalam Technological University

autor

King Gnana

• Sahrdaya College of Engineering and Technology, Thrissur, Kerala, India under APJ Abdul Kalam Technological University

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).