RESUMEN
The intraoperative registration of preoperative CT volumes is a key process of most computer-assisted orthopedic surgery (CAOS) systems. In this work, is reported a new method for automatic registration of long bones, based on the segmentation of the bone cortical in intraoperative 3D ultrasound images. A bone classifier was developed based on features, obtained from the principal component analysis of the Hessian matrix, of every voxel in an intraoperative ultrasound volume. 3D freehand ultrasound was used for the acquisition of the intraoperative ultrasound volumes. Corresponding bone surface segmentations in ultrasound and preoperative CT imaging were used for the intraoperative registration. Validation on a phantom of the tibia produced encouraging results, with a maximum mean segmentation error of 0.34â¡mm (SD=0.26â¡mm) and a registration accuracy error of 0.64â¡mm (SD=0.49â¡mm).
Asunto(s)
Huesos de la Extremidad Inferior/diagnóstico por imagen , Huesos de la Extremidad Inferior/cirugía , Diagnóstico por Imagen/métodos , Cirugía Asistida por Computador/métodos , Humanos , Procedimientos Ortopédicos/métodos , Fantasmas de ImagenRESUMEN
In this work is reported a new method for automatic segmentation of the boundary of the prostate, in transurethral ultrasound images. The scheme is based on a robust automatic initialization of an active shape model (ASM) of the prostate, which is subsequently fitted to the boundary of the gland. The initialization of the ASM is based on pixel classification to estimate the prostate region in an ultrasound image, followed by automatic adjustment - using a multipopulation genetic algorithm (MPGA) - of the initial pose of the ASM to the binary image produced by the classifier. The initial pose is next adjusted to the gray level ultrasound image, using the MPGA. After automatic initialization, the ASM is adjusted to the gray level ultrasound image to produce the final prostate contour. The method provides fast and robust segmentation of the prostate boundary. Validation results on 22 ultrasound images are reported with 1.74 mm of mean boundary error and an estimated processing time of 66 per image. Our automatic initialization method can be applied with the ASMs of different organs in various imaging modalities.
Asunto(s)
Próstata/diagnóstico por imagen , Humanos , Masculino , Modelos Anatómicos , UltrasonografíaRESUMEN
Currently, physicians are using a new technique based on radiofrequency (RF) induced hyperthermia, to treat tumors in the musculoskeletal system. This method uses a RF probe, which is placed inside the tumor, which in turn is heated within the active volume of the probe, eliminating in this way the tumor cells without affecting healthy cells. For this treatment, the surgeon must know the exact shape and location of the tumor. Usually a nuclear magnetic resonance imaging (NMRI) study is performed before surgery. Ultrasound imaging is used to locate the tumor intraoperatively. In this work is presented a computer system to build a 3D model of the tumor and adjacent bones based on segmented images from the preoperative NMRI study. Then, during surgery, the model will be registered with the anatomy of the patient, using intraoperative ultrasound images segmented by the surgeon. This work is part of a larger project, which will be a complete computer aided surgery (CAS) system to help train physicians in radiofrequency treatment and to make the procedure more reliable and efficient.