Detector of 3-D salient points based on the dual-tree complex wavelet transform for the positioning of hippocampi meshes in magnetic resonance images

Autor(es)

Souza, Breno da Silveira ^[1] ; Poloni, Katia M. ^[1] ; Ferrari, Ricardo J. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Fed Sao Carlos, Dept Comp, Rod Washington Luis, Km 235, BR-13565905 Sao Carlos, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF NEUROSCIENCE METHODS; v. 341, JUL 15 2020.
• Citações Web of Science: 0

Resumo

Background: Brain Magnetic Resonance (MR) image segmentation methods based on deformable models depend on the initial positioning to maximize the chances of successful segmentation. To minimize this limitation, salient-point based registration is used to perform the initial positioning of brain structure meshes close to their image target representation. The analysis of brain structures (such as the hippocampus) can help in the diagnosis and follow-up of neurodegenerative diseases like Alzheimer's. Methods: We present a technique for detection and description of 3-D salient points, which combines filter response maps estimated for different scales and orientations of the dual-tree complex wavelet transform (DT-CWT). We apply our technique to detect salient points in volumetric brain MR images and use the detected points in a positioning methodology. To illustrate the applicability, we applied our method for the positioning of hippocampi meshes in 3-D brain MR images and assessed the results by overlapping the positioned meshes with manual annotations made by medical specialists. Results: Our method yielded mean values of normalized Dice Similarity Coefficient (nDSC) of 0.74/0.68 and Hausdorff Average Distance (HAD) of 0.73/0.75 for the left and right hippocampus, respectively. Comparison with Other Methods: The mean nDSC and HAD results of our detector were significantly better than the ones achieved by an Affine and a Phase Congruency (PC) guided positioning. Conclusions: The detection via DT-CWT decomposition is computationally less demanding than the detection via PC and represents a robust alternative for the positioning of mesh models. (AU)

• Processo FAPESP: 18/06049-5 - Esquema computacional automático para a detecção, identificação e classificação de alterações estruturais cerebrais em imagens de ressonância magnética para auxílio ao diagnóstico de pacientes com comprometimento cognitivo leve e Doença de Alzheimer leve
• Beneficiário: Katia Maria Poloni
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 18/08826-9 - Desenvolvimento de técnicas de engenharia de características e aprendizagem profunda aplicadas à classificação de imagens de ressonância magnética nas classes envelhecimento cognitivo saudável, comprometimento cognitivo leve e Doença de Alzheimer
• Beneficiário: Ricardo José Ferrari
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 17/24391-0 - Detector de pontos salientes 3D baseado na transformada wavelet complexa de árvore dupla com aplicação no posicionamento de malhas deformáveis em imagens de RM do cérebro
• Beneficiário: Breno da Silveira Souza
• Modalidade de apoio: Bolsas no Brasil - Mestrado