Biomedical subjects

Torfinn Taxt

Publications and source records attributed to Torfinn Taxt.

4 recordsLinked to original sources

PubMed2006

Magnetic resonance brain perfusion imaging with voxel-specific arterial input functions.

PURPOSE: To propose an automatic method for estimating voxel-specific arterial input functions (AIFs) in dynamic contrast brain perfusion imaging. MATERIALS AND METHODS: Voxel-specific AIFs were estimated blindly using the theory of homomorphic transformations and complex cepstrum analysis. Wiener filtering was used in the subsequent deconvolution. The method was verified using simulated data and evaluated in 10 healthy adults. RESULTS: Computer simulations accurately estimated differently shaped, normalized AIFs. Simple Wiener filtering resulted in underestimation of flow values. Preliminary in vivo results showed comparable cerebral flow value ratios between gray matter (GM) and white matter (WM) when using blindly estimated voxel-specific AIFs or a single manually selected AIF. Significant differences (P < or = 0.0125) in mean transit time (MTT) and time-to-peak (TTP) in GM compared to WM was seen with the new method. CONCLUSION: Initial results suggest that the proposed method can replace the tedious and difficult task of manually selecting an AIF, while simultaneously providing better differentiation between time-dependent hemodynamic parameters.

Adult↗

PubMed2006

Iterative blind deconvolution in magnetic resonance brain perfusion imaging.

In first pass magnetic resonance brain perfusion imaging, arterial input functions are used in the deconvolution of the observed contrast concentrations to obtain quantitative hemodynamic parameters. Ideally, arterial input functions should be measured in each imaged voxel to eliminate the effects of delay and dispersion of the contrast agent from the injection site. An approach based on iterative blind deconvolution with the Richardson-Lucy algorithm is proposed for the simultaneous estimation of voxel-specific arterial input functions and voxel-specific tissue residue functions. An extended contrast concentration model was used to separate the first pass bolus from additional recirculation and leakage signals. The extended model was evaluated using in vivo data. Computer simulations examined the feasibility of iterative blind deconvolution in perfusion imaging. Preliminary in vivo results from a patient with fibromuscular dysplasia showed territories with delayed/dispersed arterial input functions that coincided with the location of territories supplied by collateral circulation as described from the complete radiologic examination. Higher flow values and shorter mean transit times compared to conventional methods were obtained in these areas, suggesting that the effects of dispersion were minimized. The in vivo estimated arterial input functions visualized the patient's blood supply patterns as a function of time.

Adult↗

PubMed2006

High-resolution ultrasonic imaging using fast two-dimensional homomorphic filtering.

A new method for two-dimensional deconvolution of medical ultrasonic images is presented. The spatial resolution of the deconvolved images is much higher compared to the common images of the fundamental and second harmonic. The deconvolution also results in a more distinct speckle pattern. Unlike the most published deconvolution algorithms for ultrasonic images, the presented technique can be implemented using currently available hardware in real-time imaging, with a rate up to 50 frames per second. This makes it attractive for application in the current ultrasound scanners. The algorithm is based on two-dimensional homomorphic deconvolution with simplified assumptions about the point spread function. Broadband radio frequency image data are deconvolved instead of common fundamental harmonic data. Thus, information of both the first and second harmonics is used. The method was validated on image data recorded from a tissue-mimicking phantom and on clinical image data.

Algorithms↗

PubMed2004

Superresolution of ultrasound images using the first and second harmonic signal.

This paper presents a new method of blind two-dimensional (2-D) homomorphic deconvolution and speckle reduction applied to medical ultrasound images. The deconvolution technique is based on an improved 2-D phase unwrapping scheme for pulse estimation. The input images are decomposed into minimum-phase and allpass components. The 2-D phase unwrapping is applied only to the allpass component. The 2-D phase of the minimum-phase component is derived by a Hilbert transform. The accuracy of 2-D phase unwrapping is also improved by processing small (16 x 16 pixels) overlapping subimages separately. This takes the spatial variance of the ultrasound pulse into account. The deconvolution algorithm is applied separately to the first and second harmonic images, producing much sharper images of approximately the same resolution and different speckle patterns. Speckle reduction is made by adding the envelope images of the deconvolved first and second harmonic images. Neither the spatial resolution nor the frame rate decreases, as the common compounding speckle reduction techniques do. The method is tested on sequences of clinical ultrasound images, resulting in high-resolution ultrasound images with reduced speckle noise.

Algorithms↗