An advanced MRI and MRSI data fusion scheme for enhancing unsupervised brain tumor differentiation
Proton Magnetic Resonance Spectroscopic Imaging ( 1 H MRSI) has shown great potential in tumor diagnosis since it provides localized biochemical information discriminating different tissue types, though it typically has low spatial resolution. Magnetic Resonance Imaging (MRI) is widely used in tumor diagnosis as an in vivo tool due to its high resolution and excellent soft tissue discrimination. This paper presents an advanced data fusion scheme for brain tumor diagnosis using both MRSI and MRI data to improve the tumor differentiation accuracy of MRSI alone. Non-negative Matrix Factorization (NMF) of the spectral feature vectors from MRSI data and the image fusion with MRI based on wavelet analysis are implemented jointly. Hence, it takes advantage of the biochemical tissue discrimination of MRSI as well as the high resolution of MRI. The feasibility of the proposed frame work is validated by comparing with the expert delineations, giving mean correlation coefficients for the tumor source of 0.97 and the Dice score of tumor region overlap of 0.90. These results compare favorably against those obtained with a previously proposed NMF method where MRSI and MRI are integrated by stacking the MRSI and MRI features.
- 원문이 없습니다.
- DOI : http://dx.doi.org/10.1016/j.compbiomed.2016.12.017
- Elsevier : 저널> 권호 > 논문
유료 다운로드의 경우 해당 사이트의 정책에 따라 신규 회원가입, 로그인, 유료 구매 등이 필요할 수 있습니다. 해당 사이트에서 발생하는 귀하의 모든 정보활동은 NDSL의 서비스 정책과 무관합니다.
NDSL에서는 해당 원문을 복사서비스하고 있습니다. 위의 원문복사신청 또는 장바구니 담기를 통하여 원문복사서비스 이용이 가능합니다.
- 이 논문과 함께 출판된 논문 + 더보기