Biomedical subjects

Jasjit S Suri

Publications and source records attributed to Jasjit S Suri.

11 recordsLinked to original sources

PubMed2006

Heart rate variability: a review.

Heart rate variability (HRV) is a reliable reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, they provide a powerful means of observing the interplay between the sympathetic and parasympathetic nervous systems. It shows that the structure generating the signal is not only simply linear, but also involves nonlinear contributions. Heart rate (HR) is a nonstationary signal; its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random-during certain intervals of the day. It is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Hence, HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. Therefore, the HRV signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. In this paper, we have discussed the various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV.

Alcohol Drinking↗

PubMed2006

Breast image registration techniques: a survey.

Breast cancer is the most common type of cancer in women worldwide. Image registration plays an important role in breast cancer detection. This paper gives an overview of the current state-of-the-art in the breast image registration techniques. For the intramodality registration techniques, X-ray, MRI, and ultrasound are the primary focuses of interest. Intermodality techniques will cover the combination of different modalities. Validation of breast registration methods is also discussed.

Breast↗

PubMed2005

Plaque imaging using ultrasound, magnetic resonance and computer tomography: a review.

Different classifications have been proposed in the literature for the characterization of atherosclerotic plaque morphology, resulting in considerable confusion. For example plaques containing medium of high level uniform echoes were classified as homogeneous by others and correspond closely to dense and calcified plaques, other types. This survey is to understand different types of plaque when imaged using ultrasound and MR.

Humans↗

PubMed2005

Inter- and Intra-Observer Variability Assessment of in Vivo Carotid Plaque Burden Quantification Using Multi-Contrast Dark Blood MR Images.

UNLABELLED: The chapter presents the research to test the hypotheses that (1) vessel wall volume measurements from dark blood MR images with multiple contrast-weightings (T1W, T2W and PDW) are highly reproducible, and that (2) the intra-observer and inter-observer variability of carotid wall volume measurements will be less than those obtained with maximum wall area (MaxWA) measurements. METHODS: Sixteen patients (aged 72 +/- 7years) with carotid stenosis documented by duplex ultrasound were recruited for the study. Dark blood T1W, PDW and T2W MR images were used to measure carotid wall volume and MaxWA by two independent observers for inter-observer and intra-observer variability assessment. RESULTS: The intra-observer absolute difference of carotid wall volume for T1W, T2W and PDW images were 67.3 +/- 47.5 mm(3) (2.3 +/- 1.8%), 63.2 +/- 52.2 mm(3) (2.0 +/- 1.3%), and 69.8 +/- 45.2 mm(3) (2.4 +/- 1.7%) respectively. The inter-observer absolute difference of carotid wall volume for T1W, T2W and PDW images were 103.5 +/- 141.8 mm(3) (3.0 +/- 3.1%), 95.9 +/- 102.1 mm(3) (3.1 +/- 2.6%), and 132.1 +/- 87.8 mm(3) (4.3 +/- 2.7%) respectively. The intra-observer absolute difference of carotid MaxWA for T1W, T2W and PDW images were 6.9 +/- 5.0 mm(2) (4.2 +/- 2.9%), 5.1 +/- 4.2 mm(2) (3.1 +/- 2.3%) and 7.5 +/- 4.7 mm(2) (4.2 +/- 2.7%) respectively. The inter-observer absolute difference of carotid MaxWA for T1W, T2W and PDW images were 9.5 +/- 4.2 mm(2) (5.8 +/- 2.3%), 6.4 +/- 6.1 mm(2) (3.8 +/- 3.1%) and 10.8 +/- 7.3 mm(2) (6.1 +/- 3.7%) respectively. Both intra- and inter-observer variability in carotid volume measurement tend to be smaller than that in carotid MaxWA measurement with intraclass correlation coefficients ranged 0.932 to 0.987 for volume measurement and 0.822 to 0.946 for MaxWA measurement.

Carotid Artery Diseases↗

PubMed2005

Three-Dimensional Volume Registration of Carotid MR Images.

This chapter describes automatic three-dimensional registration techniques for magnetic resonance images of carotid vessels. The immediate applications include atherosclerotic plaque characterization and plaque burden quantification vector-based segmentation using dark blood MR images having multiple contrast weightings (proton density (PD), T1, and T2). Another application is the measurement of disease progression and regression with drug trials. A normalized mutual information registration algorithm is applied to compensate movements between image acquisitions. PD, T1, and T2 images were acquired from patients and volunteers and then matched for image analysis. Visualization methods such as contour overlap showed that vessels well aligned after registration. Distance measurements from the landmarks indicated that the registration method worked well with an error of less than 1-mm.

Algorithms↗

PubMed2005

Economic impact of telemedicine: a survey.

The economic evaluation of telemedicine has faced difficulties, both in terms of the effectiveness and cost-benefit analyses. The main challenges that lie ahead for economic assessment are: (a) technological changes; (b) sustainability of applications; (c) availability of outcomes and other patient data; (d) generalisability of evaluation results. These challenges have lead to an unsatisfactory modeling of cost analysis of teleradiology systems versus non-teleradiology (visiting radiology services) applications.This paper presents the analysis on the impact of telemedicine on health care. It particularly emphasizes a model for teleradiology cost systems. We study and compare cost analysis of teleradiology system versus non-teleradiology systems. Finally, a model is presented which is made viable for computing the number of patients needed to demonstrate the viability of the telemedicine systems.We conclude the following: (a) that large number of patients is needed to validate the economic impact of telemedicine services; (b) cultural change in USA will bring most prominent effect in improving health care thereby bringing health care costs down. This when combined with improving cost effective technology like telemedicine services will bring the overall health care costs down.

Cost-Benefit Analysis↗

PubMed2005

Fischer's Fused Full Field Digital Mammography and Ultrasound System (FFDMUS).

It has been well established that X-ray modality when combined with ultrasound modality increases sensitivity and specificity of breast lesion detections. Under the NIH grant, Fischer has developed a fused full-field digital mammography and ultrasound system (FFDMUS), which has ability to acquire 2-D X-ray mammogram and 3-D ultrasound images simultaneously. This novel technology generates co-registered breast images of X-ray and ultrasound images. The co-registration error between X-ray and ultrasound images acquired is within 2.00 mm in scan direction, and is 0.5 mm in anterior-posterior direction. We did the performance evaluation of the system, and concluded that the ultrasound image qualities from FFDMUS and Hand-held ultrasound (HHUS) are comparable, and the X-ray image qualities from FFDMUS and SenoScan(R) are also comparable. We also developed a preliminary CAD registration and segmentation system for FFDMUS datasets.

Breast↗

PubMed2002

Shape recovery algorithms using level sets in 2-D/3-D medical imagery: a state-of-the-art review.

The class of geometric deformable models, also known as level sets, has brought tremendous impact to medical imagery due to its capability of topology preservation and fast shape recovery. In an effort to facilitate a clear and full understanding of these powerful state-of-the-art applied mathematical tools, this paper is an attempt to explore these geometric methods, their implementations and integration of regularizers to improve the robustness of these topologically independent propagating curves/surfaces. This paper first presents the origination of level sets, followed by the taxonomy of level sets. We then derive the fundamental equation of curve/surface evolution and zero-level curves/surfaces. The paper then focuses on the first core class of level sets, known as "level sets without regularizers." This class presents five prototypes: gradient, edge, area-minimization, curvature-dependent and application driven. The next section is devoted to second core class of level sets, known as "level sets with regularizers." In this class, we present four kinds: clustering-based, Bayesian bidirectional classifier-based, shape-based and coupled constrained-based. An entire section is dedicated to optimization and quantification techniques for shape recovery when used in the level set framework. Finally, the paper concludes with 22 general merits and four demerits on level sets and the future of level sets in medical image segmentation. We present applications of level sets to complex shapes like the human cortex acquired via MRI for neurological image analysis.

Algorithms↗

PubMed2002

White and black blood volumetric angiographic filtering: ellipsoidal scale-space approach.

Prefiltering is a critical step in three-dimensional (3-D) segmentation of the blood vessel and its display (see the recent book by Suri et al.). This paper presents a scale-space approach for filtering the white blood and black blood angiographic volumes and its implementation issues. The raw MR angiographic volume is first converted to isotropic volume followed by 3-D higher order separable Gaussian derivative convolution with known scales to generate edge volume. The edge volume is then run by the directional processor at each voxel where the eigenvalues of the 3-D ellipsoid are computed. The vessel score per voxel is then estimated based on these three eigenvalues which suppress the nonvasculature and background structures yielding the filtered volume. The filtered volume is ray-cast to generate the maximum intensity projection images for display. The performance of the system is evaluated by computing the mean, variance, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) images. The system is run over 20 patient studies from different areas of the body such as the brain, abdomen, kidney, knee, and ankle. The computer program takes around 150 s of processing time per study for a data size of 512 x 512 x 194, which includes the complete performance evaluation. We also compare our strategy with the recently published MR filtering algorithms by Alexander et al. and Sun et al.

Algorithms↗

PubMed2002

A review on MR vascular image processing: skeleton versus nonskeleton approaches: part II.

Vascular segmentation has recently been given much attention. This review paper has two parts. Part I of this review focused on the physics of magnetic resonance angiography (MRA) and prefiltering techniques applied to MRA. Part II of this review presents the state-of-the-art overview, status, and new achievements in vessel segmentation algorithms from MRA. The first part of this review paper is focused on the nonskeleton or direct-based techniques. Here, we present eight different techniques along with their mathematical foundations, algorithms and their pros and cons. We will also focus on the skeleton or indirect-based techniques. We will discuss three different techniques along with their mathematical foundations, algorithms and their pros and cons. This paper also includes a clinical discussion on skeleton versus nonskeleton-based segmentation techniques. Finally, we shall conclude this paper with the possible challenges, the future, and a brief summary on vascular segmentation techniques.

Algorithms↗

PubMed2002

A review on MR vascular image processing algorithms: acquisition and prefiltering: part I.

Vascular segmentation has recently been given much attention. This review paper has two parts. Part I focuses on the physics of magnetic resonance angiography (MRA) generation and prefiltering techniques applied to MRA data sets. Part II of the review focuses on the vessel segmentation algorithms. The first section of this paper introduces the five different sets of receive coils used with the MRI system for magnetic resonance angiography data acquisition. This section then presents the five different types of the most popular data acquisition techniques: time-of-flight (TOF), phase-contrast, contrast-enhanced, black-blood, T2-weighted, and T2*-weighted, along with their pros and cons. Section II of this paper focuses on prefiltering algorithms for MRA data sets. This is necessary for removing the background nonvascular structures in the MRA data sets. Finally, the paper concludes with a clinical discussion on the challenges and the future of the data acquisition and the automated filtering algorithms.

Algorithms↗