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Jayaram K Udupa

Publications and source records attributed to Jayaram K Udupa.

At least 19 recordsLinked to original sources
PubMed2006

Comparing MR image intensity standardization against tissue characterizability of magnetization transfer ratio imaging.

PURPOSE: To evaluate existing methods of standardization by exploiting the well-known tissue characterizing property of magnetization transfer ratio (MTR) values obtained from MT imaging, and compare the tissue characterizability of standardized T2, proton density (PD), and T1 images against the MTR images. MATERIALS AND METHODS: Image intensity standardization is a postprocessing method that was designed to correct for acquisition-to-acquisition signal intensity variations (nonstandardness) inherent in magnetic resonance (MR) images. The main idea of this technique is to deform the volume image histogram of each study to match a standard histogram, and to utilize the resulting transformations to map the image intensities into a standard scale. The method has been shown to produce a significant gain in similarity of resulting images and to achieve numeric tissue characterization. In this work we compared PD-, T2-, and T1-weighted images before and after standardization with the corresponding MT images for 10 patient MRI studies of the brain, in terms of the normalized median values on the corresponding image histograms. RESULTS: No statistically significant difference was observed between the standardized PD-, T2-, and T1-weighted images and the corresponding MTR images. However, a statistically significant difference was found between the pre- and poststandardized PD-, T2-, and T1-weighted images, and between the prestandardized PD-, T2-, and T1-weighted images and the corresponding MTR images. CONCLUSION: These results suggest that standardized T2, PD, and T1 images and their tissue-specific intensity signatures may be useful for characterizing disease.

Brain↗
PubMed2006

A framework for evaluating image segmentation algorithms.

The purpose of this paper is to describe a framework for evaluating image segmentation algorithms. Image segmentation consists of object recognition and delineation. For evaluating segmentation methods, three factors-precision (reliability), accuracy (validity), and efficiency (viability)-need to be considered for both recognition and delineation. To assess precision, we need to choose a figure of merit, repeat segmentation considering all sources of variation, and determine variations in figure of merit via statistical analysis. It is impossible usually to establish true segmentation. Hence, to assess accuracy, we need to choose a surrogate of true segmentation and proceed as for precision. In determining accuracy, it may be important to consider different 'landmark' areas of the structure to be segmented depending on the application. To assess efficiency, both the computational and the user time required for algorithm training and for algorithm execution should be measured and analyzed. Precision, accuracy, and efficiency factors have an influence on one another. It is difficult to improve one factor without affecting others. Segmentation methods must be compared based on all three factors, as illustrated in an example wherein two methods are compared in a particular application domain. The weight given to each factor depends on application.

Algorithms↗
PubMed2006

New methods of MR image intensity standardization via generalized scale.

Image intensity standardization is a post-acquisition processing operation designed for correcting acquisition-to-acquisition signal intensity variations (non-standardness) inherent in Magnetic Resonance (MR) images. While existing standardization methods based on histogram landmarks have been shown to produce a significant gain in the similarity of resulting image intensities, their weakness is that in some instances the same histogram-based landmark may represent one tissue, while in other cases it may represent different tissues. This is often true for diseased or abnormal patient studies in which significant changes in image intensity characteristics may occur. In an attempt to overcome this problem, in this paper, we present two new intensity standardization methods based on two scale concepts developed in Madabhushi et al. [Computer Vision Image Understanding 101, 100-121 (2006)] for image processing applications. These scale concepts are utilized in this paper to accurately determine principal tissue regions within MR images. Landmarks derived from these regions are used to perform intensity standardization. The new methods were qualitatively and quantitatively evaluated on a total of 67 clinical three dimensional (3D) MR images corresponding to four different protocols and to normal, Multiple Sclerosis (MS), and brain tumor patient studies. The new scale-based methods were found to be better than the existing methods, with a significant improvement observed for severely diseased and abnormal patient studies.

Algorithms↗
PubMed2006

Determining lesion size in osteonecrosis of the femoral head.

BACKGROUND: Several studies have documented that the size of the osteonecrotic lesion in the femoral head is an essential parameter in determining prognosis and treatment. There are several methods currently available to measure lesion size, but no general agreement as to which is most useful. In the present study, three different radiographic methods for determining lesion size were evaluated and compared. METHODS: Anteroposterior and lateral radiographs of forty-two hips with osteonecrosis were examined. The extent of osteonecrotic involvement of the femoral head was determined through the use of three different methods: the volume of necrosis by quantitative digital image analysis, and the angular measurements described by Kerboul et al. and Koo and Kim. Graphs were constructed to demonstrate these relationships. RESULTS: Volumetric measurement appeared to be the most reliable. There was only a rough correlation with angular measurements. Several sources of error were noted when simple angular measurements of irregular, three-dimensional lesions were used. The Kerboul method routinely overestimated lesion size and designated 81% of the lesions as "large." The modified Koo and Kim method provided a more even distribution of lesion size and correlated with volumetric measurements in 74% of hips (thirty-one of forty-two hips). CONCLUSIONS: Quantitative volumetric measurements appear to be the most reliable method to measure the true size of a three-dimensional osteonecrotic lesion of the femoral head. Volumetric measurement is more accurate than angular measurement and can be performed easily with modern technology. Angular measurements, although somewhat simpler to use than volumetric measurements, may provide only a rough estimate of lesion size, partly due to the considerable differences in outline or location of the necrotic segments. Nevertheless, determination of lesion size must be part of a comprehensive system of staging of this disease, which includes the evaluation of other parameters, such as the extent and degree of articular surface involvement and the status of the hip joint and the acetabulum. LEVEL OF EVIDENCE: Diagnostic Level III. See Instructions to Authors on jbjs.org for a complete description of levels of evidence.

Body Weights and Measures↗
PubMed2005

Computational fluid dynamics modeling of the upper airway of children with obstructive sleep apnea syndrome in steady flow.

Computational fluid dynamic (CFD) analysis was used to model the effect of airway geometry on internal pressure in the upper airway of three children with obstructive sleep apnea syndrome (OSAS), and three controls. Model geometry was reconstructed from magnetic resonance images obtained during quiet tidal breathing, meshed with an unstructured grid, and solved at normative peak resting flow. The unsteady Reynolds-averaged Navier-Stokes equations were solved with steady flow boundary conditions in inspiration and expiration, using a two-equation low-Reynolds number turbulence model. Model results were validated using an in-vitro scale model, unsteady flow simulation, and reported nasal resistance measurements in children. Pharynx pressure drop strongly correlated to airway area restriction. Inspiratory pressure drop was primarily proportional to the square of flow, consistent with pressure losses due to convective acceleration caused by area restriction. On inspiration, in OSAS pressure drop occurred primarily between the choanae and the region where the adenoids overlap the tonsils (overlap region) due to airway narrowing, rather than in the nasal passages; in controls the majority of pressure drop was in the nasal passages. On expiration, in OSAS the majority of pressure drop occurred between the oropharynx (posterior to the tongue) and overlap region, and local minimum pressure in the overlap region was near atmospheric due to pressure recovery in the anterior nasopharynx. The results suggest that pharyngeal airway shape in children with OSAS significantly affects internal pressure distribution compared to nasal resistance. The model may also help explain regional dynamic airway narrowing during expiration.

Biomechanical Phenomena↗
PubMed2005

A system for brain tumor volume estimation via MR imaging and fuzzy connectedness.

This paper presents a method for the precise, accurate and efficient quantification of brain tumor (glioblastomas) via MRI that can be used routinely in the clinic. Tumor volume is considered useful in evaluating disease progression and response to therapy, and in assessing the need for changes in treatment plans. We use multiple MRI protocols including FLAIR, T1, and T1 with Gd enhancement to gather information about different aspects of the tumor and its vicinity. These include enhancing tissue, nonenhancing tumor, edema, and combinations of edema and tumor. We have adapted the fuzzy connectedness framework for tumor segmentation in this work and the method requires only limited user interaction in routine clinical use. The system has been tested for its precision, accuracy, and efficiency, utilizing 10 patient studies. The percent coefficient of variation (% CV) in volume due to operator subjectivity in specifying seeds for fuzzy connectedness segmentation is less than 1%. The mean operator and computer time required per study for estimating the volumes of both edema and enhancing tumor is about 16 min. The software package is designed to run under operator supervision. Delineation has been found to agree with the operators' visual inspection most of the time except in some cases when the tumor is close to the boundary of the brain. In the latter case, the scalp, surgical scar, or orbital contents are included in the delineation, and an operator has to exclude this manually. The methodology is rapid, robust, consistent, yielding highly reproducible measurements, and is likely to become part of the routine evaluation of brain tumor patients in our health system.

Brain Neoplasms↗
PubMed2005

Volume rendering in the presence of partial volume effects.

In tomographic imagery, partial volume effects (PVEs) cause several artifacts in volume renditions. In X-ray computed tomography (CT), for example, soft-tissue-like pseudo structures appear in bone-to-air and bone-to-fat interfaces. Further, skin, which is identical to soft tissue in terms of CT number, obscures the rendition of the latter. The purpose of this paper is to demonstrate these phenomena and to provide effective solutions that yield significantly improved renditions. We introduce two methods that detect and classify voxels with PVE in X-ray CT. Further, a method is described to automatically peel skin so that PVE-resolved renditions of bone and soft tissue reveal considerably more detail. In the first method to address PVE, called the fraction measure (FM) method, the fraction of each tissue material in each voxel v is estimated by taking into account the intensities of the voxels neighboring v. The second method, called uncertainty principle (UP) method, is based on the following postulate (Saha and Udupa, 2001): In any acquired image, voxels with the highest uncertainty occur in the vicinity of object boundaries. The removal of skin is achieved by means of mathematical morphology. Volume renditions have been created before and after applying the methods for several patient CT datasets. A mathematical phantom experiment involving different levels of PVE has been conducted by adding different degrees of noise and blurring. A quantitative evaluation is done utilizing the mathematical phantom and clinical CT data wherein an operator carefully masked out voxels with PVE in the segmented images. All results have demonstrated the enhanced quality of display of bone and soft tissue after applying the proposed methods. The quantitative evaluations indicate that more than 98% of the voxels with PVE are removed by the two methods and the second method performs slightly better than the first. Further, skin peeling vividly reveals fine details in the soft tissue structures.

Algorithms↗
PubMed2005

Interplay between intensity standardization and inhomogeneity correction in MR image processing.

Image intensity standardization is a postprocessing method designed for correcting acquisition-to-acquisition signal intensity variations (nonstandardness) inherent in magnetic resonance (MR) images. Inhomogeneity correction is a process used to suppress the low frequency background nonuniformities (inhomogeneities) of the image domain that exist in MR images. Both these procedures have important implications in MR image analysis. The effects of these postprocessing operations on improvement of image quality in isolation has been well documented. However, the combined effects of these two processes on MR images and how the processes influence each other have not been studied thus far. In this paper, we evaluate the effect of inhomogeneity correction followed by standardization and vice-versa on MR images in order to determine the best sequence to follow for enhancing image quality. We conducted experiments on several clinical and phantom data sets (nearly 4000 three-dimensional MR images were analyzed) corresponding to four different MRI protocols. Different levels of artificial nonstandardness, and different models and levels of artificial background inhomogeneity were used in these experiments. Our results indicate that improved standardization can be achieved by preceding it with inhomogeneity correction. There is no statistically significant difference in image quality obtained between the results of standardization followed by correction and that of correction followed by standardization from the perspective of inhomogeneity correction. The correction operation is found to bias the effect of standardization. We demonstrate this bias both qualitatively and quantitatively by using two different methods of inhomogeneity correction. We also show that this bias in standardization is independent of the specific inhomogeneity correction method used. The effect of this bias due to correction was also seen in magnetization transfer ratio (MTR) images, which are naturally endowed with the standardness property. Standardization, on the other hand, does not seem to influence the correction operation. It is also found that longer sequences of repeated correction and standardization operations do not considerably improve image quality. These results were found to hold for the clinical and the phantom data sets, for different MRI protocols, for different levels of artificial nonstandardness, for different models and levels of artificial inhomogeneity, for different correction methods, and for images that were endowed with inherent standardness as well as for those that were standardized by using the intensity standardization method. Overall, we conclude that inhomogeneity correction followed by intensity standardization is the best sequence to follow from the perspective of both image quality and computational efficiency.

Algorithms↗
PubMed2004

Mandibular dimensions in children with obstructive sleep apnea syndrome.

OBJECTIVE: We hypothesized that mandibular size may play a role in the etiology of obstructive sleep apnea syndrome (OSAS) in children, since a smaller mandible may reduce airway size. We used magnetic resonance imaging to determine the mandible dimensions of children with OSAS. DESIGN: Case control study. SETTING: Tertiary-care pediatric hospital. PARTICIPANTS: Twenty-four subjects (mean age 4.9 +/- 1.7 years) with mild to moderate OSAS (Apnea Index 3.5 +/- 5.1), and 24 matched controls (mean age 4.9 +/- 1.8 years). INTERVENTION: Magnetic resonance imaging of the upper airway under sedation. MEASUREMENTS: Eight measurements were obtained from a 3-dimensional segmentation of the mandible using 3DVIEWNIX software. Measurements included length, height, width, midsymphysis menti angle, angle of mandible, enclosure area, surface area, and volume. Descriptive comparisons using Student t test and multivariate analyses of variance were performed. RESULTS: Individual measurement comparisons revealed no significant differences between groups. Multivariate analysis showed a lower bound of a 95% confidence interval for an effect size measure for "general mandibular size," including all 6 linear, the area, and the volume measurements, to be -0.25. CONCLUSION: Our study shows that a smaller mandible is not a feature in children with OSAS who do not have apparent craniofacial abnormalities.

Case-Control Studies↗
PubMed2004

Cartilage volume quantification via Live Wire segmentation.

RATIONALE AND OBJECTIVES: A reduction in cartilage volume is characteristic of osteoarthritis and hence there exists a need for an accurate and reproducible method to measure in vivo cartilage volume. Quantification of cartilage volume from magnetic resonance (MR) images requires a segmentation technique such as the user-driven "Live Wire" strategy that can reliably delineate object volumes in a time-efficient manner. In the present work, the accuracy and reproducibility of the Live Wire method for the quantification of cartilage volume in MR images is evaluated. MATERIALS AND METHODS: The accuracy of the Live Wire method was assessed by comparing the MR-based volume measurement of a patellar cartilage-shaped phantom versus data calculated via water displacement. The inter- and intra-operator reproducibility of the technique was evaluated from Live Wire segmentation of the patellar cartilage volume from fat-suppressed 3-dimensional spoiled-gradient-echo images of five healthy human volunteers performed by three operators. To provide data for analysis of inter-scan reproducibility, the human scans were repeated five times with the aid of a leg-restraining jig to minimize repositioning error. RESULTS: The volume of the patellar cartilage-shaped phantom measured via Live Wire segmentation of MR images was within 97.8% of its true volume. The average inter- and intra-operator coefficients of variation of three operators were 3.0% and 0.4%, respectively. The average inter-scan coefficient of variation of five repeated scans of each volunteer was 2.7%. CONCLUSION: The data suggest that the Live Wire strategy is an accurate, reproducible, and efficient technique to measure cartilage volume in vivo in a feasible amount of operator time.

Adult↗
PubMed2004

Iso-shaping rigid bodies for estimating their motion from image sequences.

In many medical imaging applications, due to the limited field of view of imaging devices, acquired images often include only a part of a structure. In such situations, it is impossible to guarantee that the images will contain exactly the same physical extent of the structure at different scans, which leads to difficulties in registration and in many other tasks, such as the analysis of the morphology, architecture, and kinematics of the structures. To facilitate such analysis, we developed a general method, referred to as iso-shaping, that generates structures of the same shape from segmented image sequences. The basis for this method is to automatically find a set of key points, called shape centers, in the segmented partial anatomic structure such that these points are present in all images and that they represent the same physical location in the object, and then trim the structure using these points as reference. The application area considered here is the analysis of the morphology, architecture, and kinematics of the joints of the foot from magnetic resonance images acquired at different joint positions and load conditions. The accuracy of the method is analyzed by utilizing ten data sets for iso-shaping the tibia and the fibula via four evaluative experiments. The analysis indicates that iso-shaping produces results as predicted by the theoretical framework.

Algorithms↗
PubMed2003

System for upper airway segmentation and measurement with MR imaging and fuzzy connectedness.

RATIONALE AND OBJECTIVES: The purpose of this study was to evaluate whether a computerized system developed to help delineate the upper airway and surrounding structures with magnetic resonance (MR) imaging was effective for aiding in the diagnosis of upper airway disorders in children. MATERIALS AND METHODS: The authors performed axial T2-weighted MR imaging to gather information about different aspects of the airway and its surrounding soft-tissue structures, including the adenoid and palatine tonsils, tongue, and soft palate. Images were processed and segmented to compute the architectural parameters of the airway (eg, surface description, volume, central [medial] line, and cross-sectional areas at planes perpendicular to the central line). The authors built a software package for the visualization, segmentation, registration, prefiltering, interpolation, standardization, and quantitative analysis of the airway and tonsils. RESULTS: The system was tested with 40 patient studies. For every study, the system segmented and displayed a smooth three-dimensional rendition of the airway and its central line and a plot of the cross-sectional area of the airway orthogonal to the central line as a function of the distance from one end of the central line. The precision and accuracy for segmentation was 97%. The mean time taken per study was about 4 minutes and included the operator interaction time and processing time. CONCLUSION: This method provides a robust and fast means of assessing the airway size, shape, and level of restriction, as well as a structural data set suitable for use in modeling studies of airflow and mechanics.

Algorithms↗
PubMed2003

Incorporating a measure of local scale in voxel-based 3-D image registration.

We present a new class of approaches for rigid-body registration and their evaluation in studying multiple sclerosis (MS) via multiprotocol magnetic resonance imaging (MRI). Three pairs of rigid-body registration algorithms were implemented, using cross-correlation and mutual information (MI), operating on original gray-level images, and utilizing the intermediate images resulting from our new scale-based method. In the scale image, every voxel has the local "scale" value assigned to it, defined as the radius of the largest ball centered at the voxel with homogeneous intensities. Three-dimensional image data of the head were acquired from ten MS patients for each of six MRI protocols. Images in some of the protocols were acquired in registration. The registered pairs were used as ground truth. Accuracy and consistency of the six registration methods were measured within and between protocols for known amounts of misregistrations. Our analysis indicates that there is no "best" method. For medium misregistration, the method using MI, for small add large misregistration the method using normalized cross-correlation performs best. For high-resolution data the correlation method and for low-resolution data the MI method, both using the original gray-level images, are the most consistent. We have previously demonstrated the use of local scale information in fuzzy connectedness segmentation and image filtering. Scale may also have potential for image registration as suggested by this work.

Adult↗
PubMed2002

Upper airway size analysis by magnetic resonance imaging of children with obstructive sleep apnea syndrome.

Detailed analysis of the upper airway has not been performed in children with obstructive sleep apnea. We used magnetic resonance imaging and automatic segmentation to delineate the upper airway in 20 children with obstructive sleep apnea and in 20 control subjects (age, 3.7 +/- 1.4 versus 3.9 +/- 1.7 years, respectively). We measured mean and minimal cross-sectional area, length, and volume of: (1) the total airway; (2) regions along the adenoid, tonsils, and where adenoid and tonsils overlap; and (3) 10 segments at 10% increments along the airway. The mean cross-sectional area of the total airway of the obstructive sleep apnea group was significantly smaller in comparison with the control group, 28.1 +/- 12.6 versus 47.1 +/- 18.2 mm2, respectively (p < 0.0005). Minimal cross-sectional area and airway volume were smaller in this group, 4.6 +/- 3.3 versus 15.7 +/- 12.7 mm2 (p < 0.0005), and 1,129 +/- 515 versus 1,794 +/- 846 mm3 (p < 0.005), respectively. Regional analysis suggested that the upper airway in children with obstructive sleep apnea is most restricted where adenoid and tonsils overlap. Segmental analysis demonstrated that the upper airway is restricted throughout the initial two-thirds of its length and that the narrowing is not in a discrete region adjacent to either the adenoid or tonsils, but rather in a continuous fashion along both.

Child↗
PubMed2002

The geometric architecture of the subtalar and midtarsal joints in rheumatoid arthritis based on magnetic resonance imaging.

OBJECTIVE: To compare in vivo the 3-dimensional (3-D) geometric architecture of the subtalar and midtarsal joints in normal and rheumatoid arthritic (RA) feet, using magnetic resonance imaging (MRI) analysis. METHODS: MRI was performed on 23 patients with RA, all of whom had disease activity in the subtalar and/or midtarsal joints. Image processing techniques were used to create 3-D reconstructions of the calcaneus (C), cuboid (c), navicular (N), and talus (T) bones. Twenty-four standard architectural parameters were measured from the reconstructions and were compared with data from 10 normal subjects. These parameters defined both 3-D distance and angular relationships among the 4 bones studied. Pattern classification techniques were used to establish a geometric architecture foot profile for the RA patients. The degree of individual patient fit to the new RA foot profile and to profiles for normal, pes planus, and pes cavus foot types was derived. Logistic regression was used to examine the relationship of foot architecture to inflammatory disease characteristics and physical examination variables. RESULTS: Subtalar or midtarsal pain was reported by all 23 patients, and 22 of the 23 patients presented with >/=1 clinical feature of pes planovalgus deformity. In 21 patients, ultrasonography revealed synovitis at >/=1 tarsal joint or surrounding tendon. In the RA group, the normalized distances between the geometric centroids were significantly closer for bone pairs Cc and cT and significantly distracted for bone pair CN compared with the distances in normal subjects. In RA patients (versus normal subjects), the angles subtended at the bone centroids were significantly decreased in 3 bone groups (CNc, TCN, and TNc) and significantly increased in 3 bone groups (CcN, CcT, NTc). The angles formed between the major principal axes of bone pairs CT and cT were significantly increased in RA patients compared with those in normal subjects. Pattern classification defined 11 RA feet as having normal structure and 12 as having abnormal structure. However, the abnormal feet did not fit consistently with structures defined for RA, pes planus, or pes cavus foot types. Logistic regression demonstrated that subtalar joint synovitis was the only predictive factor for abnormal subtalar and midtarsal architecture (odds ratio 19.2, 95% confidence interval 1.77-200.0). CONCLUSION: This unique 3-D MRI-based technique successfully quantified the effects of RA on the geometric architecture of the foot and the patient-specific nature of these changes. This technique can be used to provide logical therapy for correction.

Adult↗
PubMed2002

Three-dimensional bone-free rendering of the cerebral circulation by use of computed tomographic angiography and fuzzy connectedness.

INTRODUCTION: Three-dimensional computed tomographic angiography (3-D-CTA) can be used to evaluate cerebrovascular disease. A potential limitation of this technology is obscuration of vascular anatomy by bone. In view of this, we developed a method for bone-free rendering using iterative relative fuzzy connectedness (IRFC) of 3-D-CTA to examine the cerebral vasculature without the intervening cranial base. METHODS: 3-D-CTA was obtained in 10 patients with cerebrovascular disease by use of an algorithm based on IRFC. Bone structures were removed and vascular anatomy was isolated with an almost completely automated process. Bone-removed images were rendered via maximum intensity projections, compared with digital subtraction angiography, and evaluated for vascular abnormalities. RESULTS: Compared with digital subtraction angiography, IRFC 3-D-CTA successfully defined the intracranial vascular anatomy in all 10 patients. An aneurysm was identified in 6 patients, bilateral carotid-cavernous fistulae in 1 patient, and no structural abnormalities in the remaining 3 patients. CONCLUSION: In 3-D-CTA, our preliminary findings suggest that bone obscuration, one of the current limitations of CTA, can be overcome through appropriate computer algorithms. We are now working on improving the computational efficiency of these algorithms to allow routine use of IRFC 3-D-CTA in an interventional or surgical suite.

Adult↗