Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
Sensors (Basel) ; 22(22)2022 Nov 19.
Artigo em Inglês | MEDLINE | ID: mdl-36433556

RESUMO

The main goal of the approach proposed in this study, which is dedicated to the extraction of bone structures of the knee joint (femoral head, tibia, and patella), was to show a fully automated method of extracting these structures based on atlas segmentation. In order to realize the above-mentioned goal, an algorithm employed automated image-matching as the first step, followed by the normalization of clinical images and the determination of the 11-element dataset to which all scans in the series were allocated. This allowed for a delineation of the average feature vector for the teaching group in the next step, which automated and streamlined known fuzzy segmentation methods (fuzzy c-means (FCM), fuzzy connectedness (FC)). These averaged features were then transmitted to the FCM and FC methods, which were implemented for the testing group and correspondingly for each scan. In this approach, two features are important: the centroids (which become starting points for the fuzzy methods) and the surface area of the extracted bone structure (protects against over-segmentation). This proposed approach was implemented in MATLAB and tested in 61 clinical CT studies of the lower limb on the transverse plane and in 107 T1-weighted MRI studies of the knee joint on the sagittal plane. The atlas-based segmentation combined with the fuzzy methods achieved a Dice index of 85.52-89.48% for the bone structures of the knee joint.


Assuntos
Algoritmos , Imageamento por Ressonância Magnética , Imageamento por Ressonância Magnética/métodos , Articulação do Joelho/diagnóstico por imagem , Osso e Ossos , Tomografia Computadorizada por Raios X/métodos
2.
Comput Med Imaging Graph ; 78: 101664, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31635911

RESUMO

Percutaneous ablation methods are used to treat primary and metastatic liver tumors. Image guided navigation support minimally invasive interventions of rigid anatomical structures. When working with the displacement and deformation of soft tissues during surgery, as in the abdomen, imaging navigation systems are in the preliminary implementation stage. In this study a multi-stage approach has been developed to support percutaneous liver tumors ablation. It includes CT image acquisition protocol with the amplitude of respiratory motion that yields images subjected to a semi-automatic method able to deliver personalized abdominal model. Then, US probe and ablation needle calibration, as well as patient position adjustment method during the procedure for the preoperative anatomy model, have been combined. Finally, an advanced module for fusion of the preoperative CT with intraoperative US images was designed. These modules have been tested on a phantom and in the clinical environment. The final average Spatial calibration error was 1,7 mm, the average error of matching the position of the markers was about 2 mm during the entire breathing cycle, and average markers fusion error 495 mm. The obtained results indicate the possibility of using the developed method of navigation in clinical practice.


Assuntos
Neoplasias Abdominais/diagnóstico por imagem , Técnicas de Ablação , Neoplasias Hepáticas/diagnóstico por imagem , Procedimentos Cirúrgicos Minimamente Invasivos , Interpretação de Imagem Radiográfica Assistida por Computador , Cirurgia Assistida por Computador , Tomografia Computadorizada por Raios X , Neoplasias Abdominais/cirurgia , Pontos de Referência Anatômicos , Biópsia por Agulha , Humanos , Neoplasias Hepáticas/cirurgia , Planejamento de Assistência ao Paciente , Modelagem Computacional Específica para o Paciente , Imagens de Fantasmas , Radiografia Abdominal
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...