Jayaram K Udupa

Summary

Affiliation: University of Pennsylvania
Country: USA

Publications

  1. pmc CAVASS: a computer-assisted visualization and analysis software system
    George Grevera
    Department of Mathematics and Computer Science, Saint Joseph s University, 5600 City Avenue, Philadelphia, PA 19131, USA
    J Digit Imaging 20:101-18. 2007
  2. ncbi Multiple sclerosis lesion quantification using fuzzy-connectedness principles
    J K Udupa
    Department of Radiology, University of Pennsylvania, Philadelphia 19104 6021, USA
    IEEE Trans Med Imaging 16:598-609. 1997
  3. ncbi Analysis of in vivo 3-D internal kinematics of the joints of the foot
    J K Udupa
    Department of Radiology, University of Pennsylvania, Philadelphia 19104, USA
    IEEE Trans Biomed Eng 45:1387-96. 1998
  4. ncbi A framework for evaluating image segmentation algorithms
    Jayaram K Udupa
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 6021, USA
    Comput Med Imaging Graph 30:75-87. 2006
  5. ncbi 3DVIEWNIX-AVS: a software package for the separate visualization of arteries and veins in CE-MRA images
    Tianhu Lei
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 4th Floor, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 6021, USA
    Comput Med Imaging Graph 27:351-62. 2003
  6. pmc Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis
    Jiamin Liu
    Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 6021, USA
    Med Phys 35:3637-49. 2008
  7. pmc Image background inhomogeneity correction in MRI via intensity standardization
    Ying Zhuge
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 6021, USA
    Comput Med Imaging Graph 33:7-16. 2009
  8. ncbi Volume rendering in the presence of partial volume effects
    Andre Souza
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 6021, USA
    IEEE Trans Med Imaging 24:223-35. 2005
  9. ncbi System for upper airway segmentation and measurement with MR imaging and fuzzy connectedness
    Jianguo Liu
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 4th Floor, Blockley Hall, 423 Guardian Dr, Philadelphia, PA 19104 6021, USA
    Acad Radiol 10:13-24. 2003
  10. pmc Joint graph cut and relative fuzzy connectedness image segmentation algorithm
    Krzysztof Chris Ciesielski
    Department of Mathematics, West Virginia University, Morgantown, WV 26506 6310, United States Department of Radiology, MIPG, University of Pennsylvania, Blockley Hall, 4th Floor, 423 Guardian Drive, Philadelphia, PA 19104 6021, United States Electronic address
    Med Image Anal 17:1046-57. 2013

Collaborators

Detail Information

Publications46

  1. pmc CAVASS: a computer-assisted visualization and analysis software system
    George Grevera
    Department of Mathematics and Computer Science, Saint Joseph s University, 5600 City Avenue, Philadelphia, PA 19131, USA
    J Digit Imaging 20:101-18. 2007
    ....
  2. ncbi Multiple sclerosis lesion quantification using fuzzy-connectedness principles
    J K Udupa
    Department of Radiology, University of Pennsylvania, Philadelphia 19104 6021, USA
    IEEE Trans Med Imaging 16:598-609. 1997
    ..9% (based on 20 patient studies, three operators, and two trials) for volume and a mean false-negative volume fraction of 1.3%, with a 95% confidence interval of 0%-2.8% (based on ten patient studies)...
  3. ncbi Analysis of in vivo 3-D internal kinematics of the joints of the foot
    J K Udupa
    Department of Radiology, University of Pennsylvania, Philadelphia 19104, USA
    IEEE Trans Biomed Eng 45:1387-96. 1998
    ..Some of the 3-D kinematic animations generated using the methods of this paper for normal joints can be seen at: http:(/)/www.mipg.upenn.edu...
  4. ncbi A framework for evaluating image segmentation algorithms
    Jayaram K Udupa
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 6021, USA
    Comput Med Imaging Graph 30:75-87. 2006
    ..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...
  5. ncbi 3DVIEWNIX-AVS: a software package for the separate visualization of arteries and veins in CE-MRA images
    Tianhu Lei
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 4th Floor, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 6021, USA
    Comput Med Imaging Graph 27:351-62. 2003
    ..To date, it seems to be the only software package (using an image processing approach) available for artery and vein separation of the human vascular system for routine use in a clinical setting...
  6. pmc Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis
    Jiamin Liu
    Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 6021, USA
    Med Phys 35:3637-49. 2008
    ..2%-0.7%. The method requires 1-2 minutes of operator time and 6-7 min of computer time per data set, which makes it significantly more efficient than live wire-the method currently available for the task that can be used routinely...
  7. pmc Image background inhomogeneity correction in MRI via intensity standardization
    Ying Zhuge
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 6021, USA
    Comput Med Imaging Graph 33:7-16. 2009
    ..These tests and a comparison with the method of non-parametric non-uniform intensity normalization (N3) indicate that the method is effective in background intensity inhomogeneity correction and may have a slight edge over the N3 method...
  8. ncbi Volume rendering in the presence of partial volume effects
    Andre Souza
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 6021, USA
    IEEE Trans Med Imaging 24:223-35. 2005
    ..Further, skin peeling vividly reveals fine details in the soft tissue structures...
  9. ncbi System for upper airway segmentation and measurement with MR imaging and fuzzy connectedness
    Jianguo Liu
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 4th Floor, Blockley Hall, 423 Guardian Dr, Philadelphia, PA 19104 6021, USA
    Acad Radiol 10:13-24. 2003
    ....
  10. pmc Joint graph cut and relative fuzzy connectedness image segmentation algorithm
    Krzysztof Chris Ciesielski
    Department of Mathematics, West Virginia University, Morgantown, WV 26506 6310, United States Department of Radiology, MIPG, University of Pennsylvania, Blockley Hall, 4th Floor, 423 Guardian Drive, Philadelphia, PA 19104 6021, United States Electronic address
    Med Image Anal 17:1046-57. 2013
    ....
  11. doi PET/MR imaging: technical aspects and potential clinical applications
    Drew A Torigian
    Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 4283, USA
    Radiology 267:26-44. 2013
    ....
  12. pmc Image filtering via generalized scale
    Andre Souza
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Fourth Floor, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 6021, United States
    Med Image Anal 12:87-98. 2008
    ..Qualitative experiments based on both phantom and patient magnetic resonance images demonstrate that the generalized scale-based approach leads to better preservation of fine details and edges...
  13. ncbi Iso-shaping rigid bodies for estimating their motion from image sequences
    Punam K Saha
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 6021, USA
    IEEE Trans Med Imaging 23:63-72. 2004
    ..The analysis indicates that iso-shaping produces results as predicted by the theoretical framework...
  14. ncbi A system for brain tumor volume estimation via MR imaging and fuzzy connectedness
    Jianguo Liu
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, 4th Floor, Blockley Hall, 423 Guardian Drive, PA 19104 6021, USA
    Comput Med Imaging Graph 29:21-34. 2005
    ..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...
  15. pmc MR Image Analytics to Characterize the Upper Airway Structure in Obese Children with Obstructive Sleep Apnea Syndrome
    Yubing Tong
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
    PLoS ONE 11:e0159327. 2016
    ....
  16. pmc Retrospective 4D MR image construction from free-breathing slice Acquisitions: A novel graph-based approach
    Yubing Tong
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104 United States
    Med Image Anal 35:345-359. 2017
    ..This paper presents a novel graph-based technique for compiling the best 4D image volume representing the thorax over one respiratory cycle from slice images acquired during unencumbered natural tidal-breathing of pediatric TIS patients...
  17. pmc Minimally interactive segmentation of 4D dynamic upper airway MR images via fuzzy connectedness
    Yubing Tong
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
    Med Phys 43:2323. 2016
    ..No viable methods have been developed to date to solve this problem. In this paper, the authors demonstrate a practical solution by employing an iterative relative fuzzy connectedness delineation algorithm as a tool...
  18. doi Quantitative normal thoracic anatomy at CT
    Monica M S Matsumoto
    Medical Image Processing Group, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, United States
    Comput Med Imaging Graph 51:1-10. 2016
    ..The proposed method provides new, objective, and usable knowledge about anatomy whose utility in building body-wide models toward AAR has been demonstrated in other studies. ..
  19. doi Automatic anatomy recognition in whole-body PET/CT images
    Huiqian Wang
    College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China and Medical Image Processing Group Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
    Med Phys 43:613. 2016
    ..Image Anal. 18, 752-771 (2014)] to PET/CT images. Their goal was to test what level of object localization accuracy can be achieved on PET/CT compared to that achieved on diagnostic CT images...
  20. doi Feasibility of estimation of brain volume and 2-deoxy-2-(18)F-fluoro-D-glucose metabolism using a novel automated image analysis method: application in Alzheimer's disease
    Erik S Musiek
    Department of Neurology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104, USA
    Hell J Nucl Med 15:190-6. 2012
    ..In conclusion, our findings suggest that ROVER may serve as a useful quantitative adjunct to visual or regional assessment and aid analysis of whole-brain metabolism in AD and other neurologic and psychiatric diseases...
  21. ncbi Three-dimensional bone-free rendering of the cerebral circulation by use of computed tomographic angiography and fuzzy connectedness
    John M Abrahams
    Department of Neurosurgery, The Hospital of the University of Pennsylvania, Philadelphia 19104, USA
    Neurosurgery 51:264-8; discussion 268-9. 2002
    ..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...
  22. pmc Subject-specific models of the hindfoot reveal a relationship between morphology and passive mechanical properties
    Carl W Imhauser
    Department of Mechanical Engineering and Mechanics, Drexel University, 34th and Chestnut Streets, Philadelphia, PA 19104, USA
    J Biomech 41:1341-9. 2008
    ..The results suggest that individualized subject-specific treatment procedures for ankle complex disorders are potentially superior to a one-size-fits-all approach...
  23. pmc Chest Fat Quantification via CT Based on Standardized Anatomy Space in Adult Lung Transplant Candidates
    Yubing Tong
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
    PLoS ONE 12:e0168932. 2017
    ....
  24. pmc Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images
    Jayaram K Udupa
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 423 Guardian Drive, Blockley Hall, 4th Floor, Philadelphia, PA 19104, United States Electronic address
    Med Image Anal 18:752-71. 2014
    ....
  25. ncbi 3D airway segmentation via hyperpolarized 3He gas MRI by using scale-based fuzzy connectedness
    Binquan Wang
    BI, Stellar Chance Laboratories, Metabolic Magnetic Resonance Research and Computing Center, Department of Radiology, Hospital of the University of Pennsylvania, 422 Curie Boulevard, Philadelphia, PA 19104, USA
    Comput Med Imaging Graph 28:77-86. 2004
    ..The total operator and computational time required per study are on the average 2 and 20 min...
  26. pmc Optimization of abdominal fat quantification on CT imaging through use of standardized anatomic space: a novel approach
    Yubing Tong
    Department of Radiology, Medical Image Processing Group, University of Pennsylvania, Philadelphia, Pennsylvania 19104 6021
    Med Phys 41:063501. 2014
    ..calculation from different subjects are at the same anatomic location? Are there combinations of multiple slices (not necessarily contiguous) whose area sum correlates better with volume than does single slice area with volume?..
  27. doi In vivo quantification of pulmonary inflammation in relation to emphysema severity via partial volume corrected (18)F-FDG-PET using computer-assisted analysis of diagnostic chest CT
    Drew A Torigian
    Department of Radiology Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
    Hell J Nucl Med 16:12-8. 2013
    ....
  28. ncbi Detection of age-related changes in thoracic structure and function by computed tomography, magnetic resonance imaging, and positron emission tomography
    David S Well
    Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104 4283, USA
    Semin Nucl Med 37:103-19. 2007
    ..Lung metabolic volumetric products were not noted to significantly change with increasing BMI or with increasing age. In this work, we also review the literature regarding normal structural and functional changes in the thorax with age...
  29. ncbi Estimation of tumor volume with fuzzy-connectedness segmentation of MR images
    Gul Moonis
    Neuroradiology Section, Department of Radiology, University of Pennsylvania Medical Center, Philadelphia 19104 4283, USA
    AJNR Am J Neuroradiol 23:356-63. 2002
    ..Our purpose was to adapt the fuzzy-connectedness segmentation technique to measure tumor volume. This technique requires only limited operator interaction...
  30. ncbi 3D MRA visualization and artery-vein separation using blood-pool contrast agent MS-325
    Tianhu Lei
    Department of Radiology, University of Pennsylvania, Philadelphia 19104 6021, USA
    Acad Radiol 9:S127-33. 2002
  31. doi Performance evaluation of finite normal mixture model-based image segmentation techniques
    Tianhu Lei
    Dept of Radiol, Univ of Pennsylvania, Philadelphia, PA 19104 6021, USA
    IEEE Trans Image Process 12:1153-69. 2003
    ..Theoretical and experimental results are in good agreement and indicate that, for images of moderate quality, the detection operation is robust, the parameter estimates are accurate, and the segmentation errors are small...
  32. doi Taste dysfunction in multiple sclerosis
    Richard L Doty
    Smell and Taste Center, Perelman School of Medicine, University of Pennsylvania, 5 Ravdin Building, 3400 Spruce Street, Philadelphia, PA, 19104 4823, USA
    J Neurol 263:677-88. 2016
    ..Regardless of the subject group, women outperformed men on the taste measures. These findings indicate that a sizable number of MS patients exhibit taste deficits that are associated with MS-related lesions throughout the brain...
  33. pmc Computed tomography-defined abdominal adiposity is associated with acute kidney injury in critically ill trauma patients*
    Michael G S Shashaty
    1Pulmonary, Allergy, and Critical Care Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 2Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 3Division of Traumatology, Surgical Critical Care, and Emergency Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 4Drexel University School of Public Health, Philadelphia, PA 5Renal, Electrolyte, and Hypertension Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 6Cardiovascular Medicine Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 7Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 8Center for Translational Lung Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
    Crit Care Med 42:1619-28. 2014
    ..Since body mass index is nonspecific, reflecting lean, fluid, and adipose mass, we evaluated the use of CT to determine if abdominal adiposity underlies the body mass index-acute kidney injury association...
  34. doi Kinematic magnetic resonance imaging to define the cervical facet joint space for the spine in neutral and torsion
    Nicolas V Jaumard
    Departments of Neurosurgery Bioengineering, and Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia
    Spine (Phila Pa 1976) 39:664-72. 2014
    ..Prospectively acquire magnetic resonance images of the neck in normal subjects and patients with radiculopathy to measure and compare measures of the facet joint space thickness and volume...
  35. ncbi Upper airway size analysis by magnetic resonance imaging of children with obstructive sleep apnea syndrome
    Raanan Arens
    Division of Pulmonary Medicine, Children s Hospital of Philadelphia, Philadelphia, Pennsylvania 19104 4399, USA
    Am J Respir Crit Care Med 167:65-70. 2003
    ....
  36. ncbi Cartilage volume quantification via Live Wire segmentation
    Alexander J Gougoutas
    Metabolic Magnetic Resonance Research and Computing Center, Department of Radiology, University of Pennsylvania, B1 Stellar Chance Laboratories, 422 Curie Blvd, Philadelphia, PA 19104 2045, USA
    Acad Radiol 11:1389-95. 2004
    ..In the present work, the accuracy and reproducibility of the Live Wire method for the quantification of cartilage volume in MR images is evaluated...
  37. pmc The treatment of multiple sclerosis with inosine
    Clyde E Markowitz
    Neurology Department, University of Pennsylvania, Philadelphia, PA, USA
    J Altern Complement Med 15:619-25. 2009
    ....
  38. ncbi Determining lesion size in osteonecrosis of the femoral head
    David R Steinberg
    Department of Orthopaedic Surgery, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
    J Bone Joint Surg Am 88:27-34. 2006
    ..In the present study, three different radiographic methods for determining lesion size were evaluated and compared...
  39. ncbi Magnetization transfer ratio histogram analysis of normal-appearing gray matter and normal-appearing white matter in multiple sclerosis
    Yulin Ge
    Department of Radiology, New York University School of Medicine, Neew York, NY 10016, USA
    J Comput Assist Tomogr 26:62-8. 2002
    ....
  40. ncbi Interplay between intensity standardization and inhomogeneity correction in MR image processing
    Anant Madabhushi
    Department of Biomedical Engineering, Rutgers University, 617 Bowser Road, rm 102, BME Bldg, Piscataway, NJ 08854, USA
    IEEE Trans Med Imaging 24:561-76. 2005
    ..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...
  41. ncbi New methods of MR image intensity standardization via generalized scale
    Anant Madabhushi
    Department of Biomedical Engineering, Rutgers The State University of New Jersey, 617 Bowser Road, Room 101, Piscataway, New Jersey 08854, USA
    Med Phys 33:3426-34. 2006
    ..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...
  42. ncbi Incorporating a measure of local scale in voxel-based 3-D image registration
    László G Nyúl
    Department of Applied Informatics, University of Szeged, H 6701 Szeged, Hungary
    IEEE Trans Med Imaging 22:228-37. 2003
    ..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...
  43. ncbi The geometric architecture of the subtalar and midtarsal joints in rheumatoid arthritis based on magnetic resonance imaging
    James Woodburn
    Rheumatology and Rehabilitation Research Unit, University of Leeds, Leeds, UK
    Arthritis Rheum 46:3168-77. 2002
    ..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...
  44. ncbi Mandibular dimensions in children with obstructive sleep apnea syndrome
    Patricia H Schiffman
    Division of Plastic and Reconstructive Surgery, The Children s Hospital of Philadelphia, Pennsylvania 19104 4399, USA
    Sleep 27:959-65. 2004
    ..We used magnetic resonance imaging to determine the mandible dimensions of children with OSAS...
  45. ncbi Comparing MR image intensity standardization against tissue characterizability of magnetization transfer ratio imaging
    Anant Madabhushi
    Department of Biomedical Engineering, Rutgers University, New Brunswick, New Jersey, USA
    J Magn Reson Imaging 24:667-75. 2006
    ....
  46. ncbi Medical image reconstruction, processing, visualization, and analysis: the MIPG perspective. Medical Image Processing Group
    Jayaram K Udupa
    IEEE Trans Med Imaging 21:281-95. 2002