Detecção de lesões de esclerose múltipla em imagens de ressonância magnética do tipo Fluid Attenuated Inversion Recovery (FLAIR)

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Klein, Pedro Costa lattes
Orientador(a): Pinho, Márcio Sarroglia lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Pontifícia Universidade Católica do Rio Grande do Sul
Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação
Departamento: Faculdade de Informática
País: Brasil
Palavras-chave em Português:
Área do conhecimento CNPq:
Link de acesso: http://tede2.pucrs.br/tede2/handle/tede/6780
Resumo: The white matter lesion detection is an important procedure for the diagnostic of Multiple Sclerosis in patients. As important as the detection, monitoring the progression of the disease, by calculating the volumes of the lesions, also shows itself necessary. In clinical practice, this procedure is done manually by a professional or, in many cases, only a qualitative analysis is made. The manual nature of this procedure implies in a series of deficiencies on the procedure, such as variations between diagnoses from different experts on the same subject and variation between diagnostics from the same expert to the same subject at distinct moments. Yet, the manual procedure shows itself time consuming, due the large amount of slices acquired by exam and the need for a careful analysis from the expert to quantify the lesions. In order to avoid these problems, automatic approaches for Multiple Sclerosis lesion detection and quantification using computer aided diagnostic systems are proposed. These methods, mostly, demand for the acquisition of an extra modality of magnetic resonance images, where the anatomy of the brain is evidenced, thus allowing the white matter lesion identification. This additional exam goes beyond the scope of the traditional clinical practice, which implies in additional costs and prevents the method of being applied to old exams, for monitoring the disease progression. This work proposes a method for automatic detection and segmentation of Multiple Sclerosis Lesions that uses only the modality of magnetic resonance exam adopted for clinical practice, using probabilistic atlases spatially aligned to the patient’s exams for identifying the brain structures. The results obtained through the usage of the method into a set of 24 patients and 6 healthy controls of different ages, showed that the developed method is capable of detecting white matter lesions with some precision. However, the quantification of these lesions was impaired mostly due divergences between the white matter probabilistic atlas and the real white matter region of the exams.