IEEE transactions on medical imaging
-
IEEE Trans Med Imaging · Feb 2014
Separation of bones from chest radiographs by means of anatomically specific multiple massive-training ANNs combined with total variation minimization smoothing.
Most lung nodules that are missed by radiologists as well as computer-aided detection (CADe) schemes overlap with ribs or clavicles in chest radiographs (CXRs). The purpose of this study was to separate bony structures such as ribs and clavicles from soft tissue in CXRs. To achieve this, we developed anatomically specific multiple massive-training artificial neural networks (MTANNs) combined with total variation (TV) minimization smoothing and a histogram-matching-based consistency improvement method. ⋯ This new method was compared with conventional MTANNs with a database of 110 CXRs with nodules. Our new anatomically specific MTANNs separated rib edges, ribs close to the lung wall, and the clavicles from soft tissue in CXRs to a substantially higher level than did the conventional MTANNs, while the conspicuity of lung nodules and vessels was maintained. Thus, our technique for bone-soft-tissue separation by means of our new MTANNs would be potentially useful for radiologists as well as CADe schemes in detection of lung nodules on CXRs.
-
IEEE Trans Med Imaging · Nov 2013
Evaluation and real-time monitoring of data quality in electrical impedance tomography.
Electrical impedance tomography (EIT) is a noninvasive method to image conductivity distributions within a body. One promising application of EIT is to monitor ventilation in patients as a real-time bedside tool. Thus, it is essential that an EIT system reliably provide meaningful information, or alert clinicians when this is impossible. ⋯ Additionally, we show that q may be used to compare the performance of EIT systems using phantom measurements. Results suggest that the calculated metric reflects well the quality of reconstructed EIT images for both phantom and clinical data. The proposed measure can thus be used for real-time assessment of EIT data quality and, hence, to indicate the reliability of any derived physiological information.
-
IEEE Trans Med Imaging · Jul 2013
GPU-based real-time volumetric ultrasound image reconstruction for a ring array.
Synthetic phased array (SPA) beamforming with Hadamard coding and aperture weighting is an optimal option for real-time volumetric imaging with a ring array, a particularly attractive geometry in intracardiac and intravascular applications. However, the imaging frame rate of this method is limited by the immense computational load required in synthetic beamforming. For fast imaging with a ring array, we developed graphics processing unit (GPU)-based, real-time image reconstruction software that exploits massive data-level parallelism in beamforming operations. ⋯ This frame rate is 4.5 times higher than that for our previously-developed multi-core CPU-based software. In an alternative imaging mode, it shows one B-mode image rotating about the axis and its maximum intensity projection, processed at a rate of 104 fps. This paper describes the image reconstruction procedure on the GPU platform and presents the experimental images obtained using this software.
-
IEEE Trans Med Imaging · Jun 2013
Burn depth analysis using multidimensional scaling applied to psychophysical experiment data.
In this paper a psychophysical experiment and a multidimensional scaling (MDS) analysis are undergone to determine the physical characteristics that physicians employ to diagnose a burn depth. Subsequently, these characteristics are translated into mathematical features, correlated with these physical characteristics analysis. Finally, a study to verify the ability of these mathematical features to classify burns is performed. ⋯ Additional studies have been performed comparing our system with a principal component analysis and a support vector machine classifier. Results validate the ability of the mathematical features extracted from the psychophysical experiment to classify burns into their depths. In addition, the method has been compared with another state-of-the-art method and the same database.
-
IEEE Trans Med Imaging · Apr 2013
Calculation of intravascular signal in dynamic contrast enhanced-MRI using adaptive complex independent component analysis.
Assessing tumor response to therapy is a crucial step in personalized treatments. Pharmacokinetic (PK) modeling provides quantitative information about tumor perfusion and vascular permeability that are associated with prognostic factors. A fundamental step in most PK analyses is calculating the signal that is generated in the tumor vasculature. ⋯ AC-ICA provided more accurate estimate of intravascular time-intensity curve, having smaller error between the calculated and actual intravascular time-intensity curves compared to the Mag-ICA. Furthermore, it showed higher robustness in dealing with datasets with different resolution by providing smaller variation between the results of each datasets and having smaller difference between the intravascular time-intensity curves of various resolutions. Thus, AC-ICA has the potential to be used as the intravascular time-intensity curve calculation method in PK analysis and could lead to more accurate PK analysis for tumors.