&lt;title&gt;3DVIEWNIX: an open, transportable, multidimensional, multimodality, multiparametric imaging software system&lt;/title&gt;

Udupa, Jayaram K.; Odhner, Dewey; Samarasekera, Supun; Goncalves, Roberto J.; Iyer, Kiran Nanjunda; Venugopal, K.; Furuie, S.S.

doi:10.1117/12.174042

Cited by 118 publications

(67 citation statements)

References 11 publications

(14 reference statements)

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“…An object such as a high intensity signal lesion is considered to be a fuzzily connected entity wherein every pair of voxels has a "strength of connectivity" associated with it utilized (Udupa 1994;Udupa et al 1994a;Udupa and Samarasekera 1996). This strength is a global property which determines how voxels hang together in a fuzzy way to form an object (Figure 1).…”

Section: Fuzzy Voxel Approachmentioning

confidence: 99%

“…A software system called 3DVIEWNIX in which this method was implemented was utilized in all image processing. This method requires two essential steps: In the first stage, minimal operator interaction is required and the signals are automatically detected by the computer (Udupa et al 1994a;Udupa and Samarasekera 1996). A few false positives may be included at this stage.…”

Section: Fuzzy Voxel Approachmentioning

confidence: 99%

“…To detect and quantify the volume of high intensity signals, a novel method of object delineation based on "fuzzy connectedness" was utilized (Udupa 1994;Udupa et al 1994a;Udupa and Samarasekera 1996). An object such as a high intensity signal lesion is considered to be a fuzzily connected entity wherein every pair of voxels has a "strength of connectivity" associated with it utilized (Udupa 1994;Udupa et al 1994a;Udupa and Samarasekera 1996).…”

Section: Fuzzy Voxel Approachmentioning

confidence: 99%

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Atrophy and High Intensity Lesions Complementary Neurobiological Mechanisms in Late-Life Major Depression

Kumar

Bilker

Jin

et al. 2000

Neuropsychopharmacology

166

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The primary objective of our study was to examine the role of atrophy, high intensity lesions and medical comorbidity in the pathophysiology of major depressive disorder in the elderly (late-life MDD). Our sample was comprised of 51 patients with late-life MDD and 30 non-depressed controls.All subjects were scanned on 1.5 tesla magnetic resonance imaging scanner (MRI) Depression is one of the most common mental disorders in the elderly (Alexopolous et al. 1988;Beck and Koenig 1996;Blazer et al. 1987;Blazer 1989Blazer , 1994Koenig et al. 1993;Oxman et al. 1987;Parmalee et al. 1989;Ruegg et al. 1988;Sherbourne et al. 1994). The prevalence of major depressive disorder (MDD) is estimated to be approximately 1-2 percent in community settings and strikingly higher in inpatient and long term care settings (Blazer et al. 1987;Koenig et al. 1993;Parmalee et al. 1989). The prevalence of other clinically significant forms of depression, that do not meet the severity criteria for MDD, lies between 5 and 15 percent in all major clinical settings (Beck and Koenig 1996;Blazer et al. 1987, Blazer 1994Parmalee et al. 1989). Anatomical and physiological neuroimaging approaches have been utilized to study the neurobiological correlates of MDD and minor depression in the elderly (Coffey et al. 1990;Coffey et al. 1993;Greenwald et al. 1996;Krishnan et al. 1988;Krishnan 1993;Kumar et al. 1997a;Lesser et al. 1994;Sackheim et al. 1993;Sheline et al. 1996). Glucose hypometabolism and Lesser et al. 1994;Sackheim et al. 1993). Using magnetic resonance imaging (MRI), investigators have demonstrated neuroanatomical abnormalities including smaller focal brain volumes and larger high intensity lesion volumes in patients with both late-life major and minor depression when compared with non-depressed controls (Coffey et al. 1990;Coffey et al. 1993;Greenwald et al. 1996;Krishnan et al. 1988;Krishnan 1993;Kumar et al. 1997aKumar et al. , 1997bKumar et al. , 1998Sheline et al. 1996).Despite these observations, the precise nature and extent of the neuroanatomical changes in elderly patients with MDD remains unresolved (Jeste et al. 1988;Morris and Rapoport 1990).Late-life MDD is also consistently associated with medical comorbidity (Berkman et al 1986;Gierz and Jeste 1993;Katz et al. 1994;Katz 1996;Lacro and Jeste 1994;Rodin and Voshart 1986). A broad spectrum of medical disorders including cardiovascular, musculoskeletal, gastrointestinal, pulmonary and metabolic disturbances are associated with both major and minor forms of depression (Alexopolous et al. 1988;Katz et al. 1994;Koenig et al. 1993;Lacro and Jeste 1994). Despite this association, the relationship between neuroanatomical abnormalities and medical disorders in late-life and their relative contributions to the pathophysiology of mood disorders remain unknown.In an earlier report, we demonstrated that the odds of developing MDD in late-life increased with overall medical burden and larger whole brain cerebrospinal fluid (CSF) volume (Kumar et al. 1997a). However, only global measures ...

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Section: Fuzzy Voxel Approachmentioning

confidence: 99%

Section: Fuzzy Voxel Approachmentioning

confidence: 99%

Section: Fuzzy Voxel Approachmentioning

confidence: 99%

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Atrophy and High Intensity Lesions Complementary Neurobiological Mechanisms in Late-Life Major Depression

Kumar

Bilker

Jin

et al. 2000

Neuropsychopharmacology

166

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“…Three-dimensional soft tissue and airway reconstruction was performed by 3DVIEWNIX software (Udupa et al, 1994;Arens et al, 2003).…”

Section: Image Analysismentioning

confidence: 99%

Velopharyngeal Anatomy in 22q11.2 Deletion Syndrome: A Three-Dimensional Cephalometric Analysis

Ruotolo¹,

LaRossa²,

Arens³

et al. 2005

Cleft Palate-Craniofac J

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Objective-22q11.2 deletion syndrome is the most common genetic cause of velopharyngeal dysfunction (VPD). Magnetic resonance imaging (MRI) is a promising method for noninvasive, three-dimensional (3D) assessment of velopharyngeal (VP) anatomy. The purpose of this study was to assess VP structure in patients with 22q11.2 deletion syndrome by using 3D MRI analysis.Design-This was a retrospective analysis of magnetic resonance images obtained in patients with VPD associated with a 22q11.2 deletion compared with a normal control group.Setting-This study was conducted at The Children's Hospital of Philadelphia, a pediatric tertiary care center.Patients, Participants-The study group consisted of 5 children between the ages of 2.9 and 7.9 years, with 22q11.2 deletion syndrome confirmed by fluorescence in situ hybridization analysis. All had VPD confirmed by nasendoscopy or videofluoroscopy. The control population consisted of 123 unaffected patients who underwent MRI for reasons other than VP assessment. Interventions-Axial and sagittal T1-and T2-weighted magnetic resonance images with 3-mm slice thickness were obtained from the orbit to the larynx in all patients by using a 1.5T Siemens Visions system.Outcome Measures-Linear, angular, and volumetric measurements of VP structures were obtained from the magnetic resonance images with VIDA image-processing software.Results-The study group demonstrated greater anterior and posterior cranial base and atlantodental angles. They also demonstrated greater pharyngeal cavity volume and width and lesser tonsillar and adenoid volumes.Conclusion-Patients with a 22q11.2 deletion demonstrate significant alterations in VP anatomy that may contribute to VPD. Keywords 22q11.2 deletion syndrome; magnetic resonance imaging; velopharyngeal dysfunctionNormal velopharyngeal (VP) function is dependent upon multiple factors. Neuromuscular function, velar anatomy, and overall morphology of the VP port all contribute to the process of VP valving. The structural and functional integrity of each of these factors ultimately determines the adequacy of the VP mechanism as a whole. The VP port is composed of soft tissues (e.g., adenoids, lateral and posterior pharyngeal walls, velum) and their underlying bony structures (e.g., maxilla, basicranium, upper cervical spine). Alterations in one or more of these structures may be a feature of some craniofacial syndromes and may play a critical role in the pathogenesis of associated VP dysfunction (VPD).With an estimated incidence of 1 in 4000 births, the 22q11.2 deletion syndrome, also known as velocardiofacial syndrome (VCFS), is the most common genetic cause of VPD (McDonaldMcGinn et al., 1999). Affected patients present with a spectrum of functional and anatomic abnormalities that may contribute to alterations in VP valving, including cleft palate or submucosal cleft palate, palatopharyngeal hypotonia, platybasia, adenoid hypoplasia, and cervical spine abnormalities (Havkin et al., 2000). To date, however, the relative contribution of each of th...

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“…Toward this goal, five 2D scenes , T ∈ {1, 2, 3, 4, 5}, were created by using the drawing tools supported by 3DVIEWNIX [24]. Each of these scenes contained four separate objects and a background.…”

Section: A Quantitative Evaluationmentioning

confidence: 99%

Iterative relative fuzzy connectedness for multiple objects with multiple seeds

Ciesielski

Udupa

Saha

et al. 2007

Computer Vision and Image Understanding

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In this paper we present a new theory and an algorithm for image segmentation based on a strength of connectedness between every pair of image elements. The object definition used in the segmentation algorithm utilizes the notion of iterative relative fuzzy connectedness, IRFC. In previously published research, the IRFC theory was developed only for the case when the segmentation was involved with just two segments, an object and a background, and each of the segments was indicated by a single seed. (See Udupa, Saha, Lotufo [15] and Saha, Udupa [14].) Our theory, which solves a problem of Udupa and Saha from [13], allows simultaneous segmentation involving an arbitrary number of objects. Moreover, each segment can be indicated by more than one seed, which is often more natural and easier than a single seed object identification.The first iteration step of the IRFC algorithm gives a segmentation known as relative fuzzy connectedness, RFC, segmentation. Thus, the IRFC technique is an extension of the RFC method. Although the RFC theory, due to Saha and Udupa [19], is developed in the multi object/multi seed framework, the theoretical results presented here are considerably more delicate in nature and do not use the results from [19]. On the other hand, the theoretical results from [19] are immediate consequences of the results presented here. Moreover, the new framework not only subsumes previous fuzzy connectedness descriptions but also sheds new light on them. Thus, there are fundamental theoretical advances made in this paper.We present examples of segmentations obtained via our IRFC based algorithm in the multi object/ multi seed environment, and compare it with the results obtained with the RFC based algorithm. Our results indicate that, in many situations, IRFC outperforms RFC, but there also exist instances where the gain in performance is negligible.

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<title>3DVIEWNIX: an open, transportable, multidimensional, multimodality, multiparametric imaging software system</title>

Cited by 118 publications

References 11 publications

Atrophy and High Intensity Lesions Complementary Neurobiological Mechanisms in Late-Life Major Depression

Atrophy and High Intensity Lesions Complementary Neurobiological Mechanisms in Late-Life Major Depression

Velopharyngeal Anatomy in 22q11.2 Deletion Syndrome: A Three-Dimensional Cephalometric Analysis

Iterative relative fuzzy connectedness for multiple objects with multiple seeds

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