Fichtinger, Gabor

PURPOSE: A ground-truth validation platform was developed to provide spatial correlation between ultrasound (US), temperature measurements and histopathology images to validate US based thermal ablation monitoring methods. <p>METHOD: The test-bed apparatus consists of a container box with integrated fiducial lines. Tissue samples are suspended within the box using agar gel as the fixation medium. Following US imaging, the gel block is sliced and pathology images are acquired. Interactive software segments the fiducials as well as structures of interest in the pathology and US images. The software reconstructs the regions in 3D space and performs analysis and comparison of the features identified from both imaging modalities. <p>RESULTS: The apparatus and software were constructed to meet technical requirements. Tissue samples were contoured, reconstructed and registered in the common coordinate system of fiducials. There was agreement between the sample shapes, but systematic shift of several millimeters was found between histopathology and US. This indicates that during pathology slicing shear forces tend to dislocate the fiducial lines. Softer fiducial lines and harder gel material can eliminate this problem. <p>CONCLUSION: Viability of concept was presented. Despite our straightforward approach, further experimental work is required to optimize all materials and customize software. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for tissue characterization using wavelet transform of ultrasound radio frequency (RF) echo signals. We propose the use of multiscale products of wavelet transform sequences of RF echoes to estimate the scatterer distribution in the tissue. The proposed method is based on the fact that when emitted ultrasound beams interact with scatterers in the tissue, backscattered beams contain singularities corresponding to the location of the scatterers. The singularities will exist in multiple scales of wavelet sequences of the echo signals. Therefore, peaks of wavelet transform multiscale products correspond to the location of scatterers. Estimation of scatterer spacing can be used for tissue characterization. The efficacy of the proposed method was validated in RF echo signals of in-vitro human prostate to characterize normal and cancerous tissue. The results confirm that wavelet transform multiscale products of RF echo signals contain tissue typing information that can be used as an effective tool to differentiate normal and cancerous prostate tissue.

Ultrasound image guided needle insertion is the method of choice for a wide variety of medical diagnostic and therapeutic procedures. When flexible needles are inserted in soft tissue, these needles generally follow a curved path. Segmenting the trajectory of the needles in ultrasound images will facilitate guiding them within the tissue. In this paper, a novel algorithm for curved needle segmentation in three-dimensional (3D) ultrasound images is presented. The algorithm is based on the projection of a filtered 3D image onto a two-dimensional (2D) image. Detection of the needle in the resulting 2D image determines a surface on which the needle is located. The needle is then segmented on the surface. The proposed technique is able to detect needles without any previous assumption about the needle shape, or any a priori knowledge about the needle insertion axis line.