Jayaram K Udupa

Summary

Affiliation: University of Pennsylvania
Country: USA

Publications

  1. ncbi 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. ncbi 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. ncbi 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 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
  9. 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
  10. 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

Collaborators

Detail Information

Publications31

  1. ncbi 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. ncbi 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. ncbi 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 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
    ..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...
  9. 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...
  10. 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...
  11. 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...
  12. ncbi 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 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...
  14. 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...
  15. 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...
  16. 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
  17. 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
    ..2% to 1.3%. CONCLUSIONS: Fuzzy-connected segmentation permits rapid, reliable, consistent and highly reproducible measurement of tumor volume from MR images with limited operator interaction...
  18. ncbi 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...
  19. ncbi 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
    ....
  20. 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
    ....
  21. 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
    ..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...
  22. 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...
  23. 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...
  24. 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
    ..CONCLUSION: Separate analysis of GM and WM MTR histograms may allow better detection of subtle damage and better understanding of the natural history of MS disease and ultimately the response to therapeutics...
  25. 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...
  26. 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...
  27. 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...
  28. 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
    ..CONCLUSION: These results suggest that standardized T2, PD, and T1 images and their tissue-specific intensity signatures may be useful for characterizing disease...
  29. 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...
  30. 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
    ..25. CONCLUSION: Our study shows that a smaller mandible is not a feature in children with OSAS who do not have apparent craniofacial abnormalities...
  31. 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