Curvelet initialized level set cell segmentation for touching cells in low contrast images.

Cell segmentation is an important element of automatic cell analysis. This paper proposes a method to extract the cell nuclei and the cell boundaries of touching cells in low contrast images. First, the contrast of the low contrast cell images is improved by a combination of multiscale top hat filter and h-maxima. Then, a curvelet initialized level set method has been proposed to detect the cell nuclei and the boundaries. The image enhancement results have been verified using PSNR (Peak Signal to noise ratio) and the segmentation results have been verified using accuracy, sensitivity and precision metrics. The results show improved values of the performance metrics with the proposed method.

A strategic approach for cardiac MR left ventricle segmentation.

Quantitative evaluation of cardiac function from cardiac magnetic resonance (CMR) images requires the identification of the myocardial walls. This generally requires the clinician to view the image and interactively trace the contours. Especially, detection of myocardial walls of left ventricle is a difficult task in CMR images that are obtained from subjects having serious diseases. An approach to automated outlining the left ventricular contour is proposed. In order to segment the left ventricle, in this paper, a combination of two approaches is suggested. Difference of Gaussian weighting function (DoG) is newly introduced in random walk approach for blood pool (inner contour) extraction. The myocardial wall (outer contour) is segmented out by a modified active contour method that takes blood pool boundary as the initial contour. Promising experimental results in CMR images demonstrate the potentials of our approach.

Automatic left ventricular contour extraction from cardiac magnetic resonance images using cantilever beam and random walk approach.

Heart failure is a well-known debilitating disease. From clinical point of view, segmentation of left ventricle (LV) is important in a cardiac magnetic resonance (CMR) image. Accurate parameters are desired for better diagnosis. Proper and fast image segmentation of LV is of paramount importance prior to estimation of these parameters. We prefer random walk approach over other existing techniques due to two of its advantages: (1) robustness to noise and, (2) it does not require any special condition to work. Performance of the method solely depends on the selection of initial seed and parameter ß. Problems arise while applying this method to different kind of CMR images bearing different ischemia. It is due due to their implicit geometry definitions unlike general images, where the boundary of LV in the image is not available in an explicit form. This type of images bear multi-labeled LV and the manual seed selection in these images introduces variability in the results. In view of this, the paper presents two modifications in the algorithm: (1) automatic seed selection and, (2) automatic estimation of ß from the image. The highlight of our method is its ability to succeed with minimum number of initial seeds.

Wavelet based ST-segment analysis.

A novel algorithm for ST-segment analysis is developed using the multi-resolution wavelet approach. The system detects the QRS complexes and analyses each beat using the wavelet transform to identify the characteristic points (fiducial points). These fiducial points are, iso-electric level, the J point, and onsets and offsets of the QRS complex and T wave. The algorithm determines the T onset by looking for a point of inflection between the J point and the T peak. Furthermore, detection of characteristic points by the wavelet technique reduces the effect of noise. The results show that the proposed approach gives very accurate ST levels, as compared to the conventional (empirical) technique, at higher heart rates and with different morphologies. The algorithm detects the ST-segment length in 92.3% beats with an error of 4 ms, and in 97.3% beats the error is within 8 ms. The algorithm has been implemented on a TMS320C25 based add-on DSP card connected to a PC to provide the on-line analysis and display of ST-segment data.

Beat by beat QT interval detection and characterization.

A novel algorithm for detection and analysis of QT interval, a risk factor for sudden cardiac death, is developed using the multiresolution wavelet approach. The characteristic points for detection of QT interval, i.e., the onset and offsets of the QRS complex and the T wave are detected by analyzing the wavelet transform of the ECG at particular scales. The results of the detailed study using standard data base indicate that proposed technique can be used to monitor critical heart patients for localization of problems in the duration of ventricular activation. The algorithm has been implemented on TMS320C25 based add-on DSP card to PC to provide the beat by beat analysis and display of QT interval data.

A DSP based real time system for analysis of bundle of His and late potentials using wavelet transforms.

A new system for analysis of Bundle of HIS and Late Potentials has been developed using the wavelet approach. The objective of the present research work is to develop a real-time system which does not rely on averaged data and has the capability to detect beat to beat variations in the cardiac micro-volt signals from the body surface recordings. Multiresolution wavelet analysis gives better time and frequency resolution of the signal and its implementation on DSP hardware makes the system real time. The clinical applicability of the system developed is currently being investigated with initial success on pre clinical data.

Quantitative analysis of errors due to power-line interference and base-line drift in detection of onsets and offsets in ECG using wavelets.

Timing characterisation of the ECG using wavelet transforms is a new technique in which multiscale analysis reduces the influence of noise. This technique issued to investigate the effect of noise and to estimate the errors involved in the detection of onsets and offsets of ECG waves. With appropriate choice of scales of analysis, the study shows that the errors involved in the measurement of QRS width in the presence of base-line wander are negligible. The 50 Hz power-line interference introduces a maximum error of 6.25% if it is greater than 50% of the signal amplitude. The P and T complexes are not affected by power-line interference, but the base-line wander introduces a maximum error of 9.6%. In situations with the simultaneous presence of both types of noise, the use of an optimised scale restricts the errors to within clinically acceptable limits.

DSP based enhanced data acquisition system.

Digital Signal Processing (DSP) based Enhanced Data Acquisition System for Electrocardiography/Verctorcardiography (ECG/VCG) has been developed. The system is based on Texas Instrument's TMS320C25 Digital Signal Processor which has the capability of executing 5 Million Instructions Per Second (MIPS) at peak speed. This processor provides the necessary requirements of parallel processing, instruction pipelining, execution of multiple instructions in a single clock cycle for real time data acquisition and analysis of Bio Signals. The present work describes the enhanced data acquisition system using DSP chip along with its peripherals.

An 8086-based Holter arrhythmia monitor.

Holter monitoring is a technique which involves the use of a specialized recorder to record and analyze the ECG of an ambulatory subject for a duration up to 24 h. It is used for persons who have generally normal ECG, but who experience heart disorders under some particular stress conditions. This paper describes the design of an 8086-based Holter monitor using state-of-the-art technology. The old concept of analog signal processing and cassette recording has been replaced by digital signal processing and solid state memories. The main features of the new monitor, as compared with conventional ones, is its intelligence to detect and record arrhythmias which are of clinical importance. Emphasis was placed on miniaturization and minimization of the power consumption while designing the monitor.