Prof. Punam K. Saha Profile

Prof. Punam K. Saha

Professor at Univ of Iowa

SPIE Involvement:

Conference Program Committee | Author

Publications (64)

Proceedings Article | 10 April 2023 Presentation + Paper

Automated detection of ribs in chest CT scans and assessment of changes in their morphology between Total Lung Capacity (TLC) and Residual Volume (RV)

Syed Ahmed Nadeem, Alejandro Comellas, Eric Hoffman, Punam Saha

Proceedings Volume 12468, 124680H (2023) https://doi.org/10.1117/12.2653941

KEYWORDS: Voxels, Chest, Deep learning, Image segmentation, Image processing, Lung, Computed tomography, Education and training, Chronic obstructive pulmonary disease, 3D image processing

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Proceedings Article | 4 April 2022 Presentation + Paper

CT-based segmentation of pectoral muscle using deep learning and association of computed metrics with aging and sex

Indra Narayan Dutta, Syed Ahmed Nadeem, Alejandro Comellas, Eric Hoffman, Punam Saha

Proceedings Volume 12036, 120360R (2022) https://doi.org/10.1117/12.2613073

KEYWORDS: Chest, Image segmentation, Image processing, Lung, Medical imaging, Computed tomography, Chronic obstructive pulmonary disease, 3D image processing

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Proceedings Article | 4 April 2022 Presentation + Paper

CT-based segmentation of thoracic vertebrae using deep learning and computation of the kyphotic angle

Syed Ahmed Nadeem, Alejandro Comellas, Indranil Guha, Elizabeth Regan, Eric Hoffman, Punam Saha

Proceedings Volume 12036, 1203616 (2022) https://doi.org/10.1117/12.2613065

KEYWORDS: Image processing algorithms and systems, Chest, X-ray computed tomography, Image segmentation, Image processing, Lung, Computed tomography, Reconstruction algorithms, Spine, 3D image processing

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Proceedings Article | 4 April 2022 Presentation + Paper

Clinical CT-based assessment of trabecular bone shear modulus using nonlinear finite element modelling

Indranil Guha, Xiaoliu Zhang, Punam Saha

Proceedings Volume 12036, 120361E (2022) https://doi.org/10.1117/12.2611648

KEYWORDS: Bone, Finite element methods, Computed tomography, In vivo imaging

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Generalizability of a deep learning airway segmentation algorithm to a blinded low-dose CT dataset

Syed Ahmed Nadeem, Alejandro Comellas, Eric Hoffman, Punam Saha

Proceedings Volume 11596, 115963I (2021) https://doi.org/10.1117/12.2580224

KEYWORDS: Chest, Image segmentation, Image processing, Lung, Medical imaging, Computed tomography, Physiology, Lung cancer, Chronic obstructive pulmonary disease

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Proceedings Article | 15 February 2021 Presentation + Paper

Finite element modelling of trabecular bone microstructure using emerging CT images

Indranil Guha, Chamith Rajapakse, Xiaoliu Zhang, Gregory Chang, Punam Saha

Proceedings Volume 11600, 116001C (2021) https://doi.org/10.1117/12.2580788

KEYWORDS: Modeling, Sensors, Stereoscopy, Image segmentation, Image resolution, Bone, Finite element methods, Terbium, Computed tomography, Performance modeling

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Proceedings Article | 15 February 2021 Presentation + Paper

Unsupervised GAN-CIRCLE for high-resolution reconstruction of bone microstructure from low-resolution CT scans

Indranil Guha, Syed Ahmed Nadeem, Xiaoliu Zhang, Steven Levy, James Torner, Punam Saha

Proceedings Volume 11600, 116001F (2021) https://doi.org/10.1117/12.2581068

KEYWORDS: Minerals, Scanners, Bone, Computed tomography, In vivo imaging

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Proceedings Article | 10 March 2020 Paper

Anatomical labeling of human airway branches using a novel two-step machine learning and hierarchical features

Syed Ahmed Nadeem, Eric Hoffman, Alejandro Comellas, Punam Saha

Proceedings Volume 11313, 1131312 (2020) https://doi.org/10.1117/12.2546004

KEYWORDS: Gold, Chest, Data modeling, Visualization, Image segmentation, Lung, Machine learning, Computed tomography, Image classification, Chronic obstructive pulmonary disease

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Proceedings Article | 28 February 2020 Presentation + Paper

Deep learning based high-resolution reconstruction of trabecular bone microstructures from low-resolution CT scans using GAN-CIRCLE

Indranil Guha, Syed Ahmed Nadeem, Chenyu You, Xiaoliu Zhang, Steven Levy, Ge Wang, James Torner, Punam Saha

Proceedings Volume 11317, 113170U (2020) https://doi.org/10.1117/12.2549318

KEYWORDS: X-ray computed tomography, CT reconstruction, Bone, Computed tomography, Convolution, Network architectures

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Proceedings Article | 28 February 2020 Presentation + Paper

CT-based characterization of transverse and longitudinal trabeculae and its applications

Xiaoliu Zhang, Elena Letuchy, Steven Levy, James Torner, Punam Saha

Proceedings Volume 11317, 113171F (2020) https://doi.org/10.1117/12.2549881

KEYWORDS: Minerals, X-ray computed tomography, Magnetic resonance imaging, Image segmentation, Image processing, Bone, Terbium, Computed tomography, In vivo imaging, Algorithm development

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Proceedings Article | 15 March 2019 Paper

A fully automated CT-based airway segmentation algorithm using deep learning and topological leakage detection and branch augmentation approaches

Syed Ahmed Nadeem, Eric Hoffman, Punam Saha

Proceedings Volume 10949, 109490C (2019) https://doi.org/10.1117/12.2512286

KEYWORDS: Image processing algorithms and systems, Chest, Detection and tracking algorithms, Visualization, Image segmentation, Image processing, Lung, Computed tomography, Chronic obstructive pulmonary disease, 3D image processing

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Proceedings Article | 12 March 2018 Presentation + Paper

Segmentation and assessment of structural plasticity of hippocampal dendritic spines from 3D confocal light microscopy

Subhadip Basu, Punam Kumar Saha, Ewa Baczynska, Matylda Roszkowska, Marta Magnowska, Nirmal Das, Indranil Guha, Jakub Wlodarczyk

Proceedings Volume 10578, 105780E (2018) https://doi.org/10.1117/12.2292924

KEYWORDS: Confocal microscopy, Image segmentation, Quantitative analysis, Spine, Dendrites, 3D image processing, Neurons

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Proceedings Article | 12 March 2018 Paper

MRI-based active shape model of the human proximal femur using fiducial and secondary landmarks and its validation

Xiaoliu Zhang, Cheng Chen, Sean Boone, Vivek Joshi, Arakua Welbeck, Guoyuan Liang, Gregory Chang, Punam Saha

Proceedings Volume 10578, 105781L (2018) https://doi.org/10.1117/12.2293732

KEYWORDS: Principal component analysis, Visualization, Magnetic resonance imaging, Image segmentation, Error analysis, 3D modeling, Bone, Shape analysis, Prototyping

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Proceedings Article | 2 March 2018 Paper

Topological leakage detection and freeze-and-grow propagation for improved CT-based airway segmentation

Syed Ahmed Nadeem, Eric Hoffman, Jered Sieren, Punam Saha

Proceedings Volume 10574, 105741A (2018) https://doi.org/10.1117/12.2293309

KEYWORDS: Image processing algorithms and systems, Chest, Detection and tracking algorithms, Visualization, Image segmentation, Diagnostics, Lung, Computed tomography, Reconstruction algorithms, Chronic obstructive pulmonary disease

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Proceedings Article | 13 March 2017 Paper

Robust segmentation of trabecular bone for in vivo CT imaging using anisotropic diffusion and multi-scale morphological reconstruction

Cheng Chen, Dakai Jin, Xiaoliu Zhang, Steven Levy, Punam Saha

Proceedings Volume 10137, 101371T (2017) https://doi.org/10.1117/12.2254546

KEYWORDS: Image processing algorithms and systems, Image segmentation, Image processing, Diffusion, Image resolution, Image registration, Bone, Computed tomography, In vivo imaging, Algorithm development, Anisotropic diffusion

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Proceedings Article | 13 March 2017 Paper

Direct biomechanical modeling of trabecular bone using a nonlinear manifold-based volumetric representation

Dakai Jin, Jia Lu, Xiaoliu Zhang, Cheng Chen, ErWei Bai, Punam Saha

Proceedings Volume 10137, 101371U (2017) https://doi.org/10.1117/12.2254705

KEYWORDS: Modeling, 3D image reconstruction, Image segmentation, 3D modeling, Bone, Finite element methods, Reconstruction algorithms, Biological research, In vivo imaging, Algorithm development, 3D image processing

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Osteoporosis is associated with increased fracture risk. Recent advancement in the area of in vivo imaging allows segmentation of trabecular bone (TB) microstructures, which is a known key determinant of bone strength and fracture risk. An accurate biomechanical modelling of TB micro-architecture provides a comprehensive summary measure of bone strength and fracture risk. In this paper, a new direct TB biomechanical modelling method using nonlinear manifold-based volumetric reconstruction of trabecular network is presented. It is accomplished in two sequential modules. The first module reconstructs a nonlinear manifold-based volumetric representation of TB networks from three-dimensional digital images. Specifically, it starts with the fuzzy digital segmentation of a TB network, and computes its surface and curve skeletons. An individual trabecula is identified as a topological segment in the curve skeleton. Using geometric analysis, smoothing and optimization techniques, the algorithm generates smooth, curved, and continuous representations of individual trabeculae glued at their junctions. Also, the method generates a geometrically consistent TB volume at junctions. In the second module, a direct computational biomechanical stress-strain analysis is applied on the reconstructed TB volume to predict mechanical measures. The accuracy of the method was examined using micro-CT imaging of cadaveric distal tibia specimens (N = 12). A high linear correlation (r = 0.95) between TB volume computed using the new manifold-modelling algorithm and that directly derived from the voxel-based micro-CT images was observed. Young’s modulus (YM) was computed using direct mechanical analysis on the TB manifold-model over a cubical volume of interest (VOI), and its correlation with the YM, computed using micro-CT based conventional finite-element analysis over the same VOI, was examined. A moderate linear correlation (r = 0.77) was observed between the two YM measures. This preliminary results show the accuracy of the new nonlinear manifold modelling algorithm for TB, and demonstrate the feasibility of a new direct mechanical strain-strain analysis on a nonlinear manifold model of a highly complex biological structure.

Proceedings Article | 24 February 2017 Presentation + Paper

An iterative method for airway segmentation using multiscale leakage detection

Syed Ahmed Nadeem, Dakai Jin, Eric Hoffman, Punam Saha

Proceedings Volume 10133, 1013308 (2017) https://doi.org/10.1117/12.2254507

KEYWORDS: Image processing algorithms and systems, Chest, Detection and tracking algorithms, Image segmentation, Lung, Solids, Computed tomography, Iterative methods, Lung imaging, Chronic obstructive pulmonary disease

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Proceedings Article | 29 March 2016 Paper

A semi-automatic framework of measuring pulmonary arterial metrics at anatomic airway locations using CT imaging

Dakai Jin, Junfeng Guo, Timothy Dougherty, Krishna Iyer, Eric Hoffman, Punam Saha

Proceedings Volume 9788, 978816 (2016) https://doi.org/10.1117/12.2216558

KEYWORDS: Human-machine interfaces, Veins, Statistical analysis, Image segmentation, Arteries, Lung, Spatial analysis, Computed tomography, Emphysema

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Proceedings Article | 14 February 2012 Paper

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

Zhiyun Gao, Randall Grout, Eric Hoffman, Punam Saha

Proceedings Volume 8314, 83142W (2012) https://doi.org/10.1117/12.911471

KEYWORDS: Veins, Ions, Lung, Medical imaging, Computed tomography, In vivo imaging, Neodymium, Algorithm development, Electrophoretic light scattering, Pulmonary hypertension

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Proceedings Article | 13 March 2010 Paper

A new osteophyte segmentation method with applications to an anterior cruciate ligament transection rabbit femur model via micro-CT imaging

G. Liang, J. Elkins, A. Coimbra, L. Duong, D. Williams, M. Sonka, P. Saha

Proceedings Volume 7623, 76234F (2010) https://doi.org/10.1117/12.844440

KEYWORDS: Image processing algorithms and systems, Data modeling, Surgery, Image segmentation, Interfaces, 3D modeling, Bone, Computed tomography, Prototyping, 3D image processing

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Proceedings Article | 13 March 2010 Paper

Multiscale topo-morphologic opening of arteries and veins: a validation study on phantoms and CT imaging of pulmonary vessel casting of pigs

Zhiyun Gao, Colin Holtze, Milan Sonka, Eric Hoffman, Punam Saha

Proceedings Volume 7623, 76233H (2010) https://doi.org/10.1117/12.844456

KEYWORDS: Veins, X-ray computed tomography, Image segmentation, Image processing, Arteries, Computed tomography, Reconstruction algorithms, In vivo imaging, Fuzzy logic, 3D image processing

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Proceedings Article | 30 October 2009 Paper

An improved algorithm to compute tensor scale and its application to medical image interpolation

Ziyue Xu, Milan Sonka, Punam Saha

Proceedings Volume 7497, 74971E (2009) https://doi.org/10.1117/12.851176

KEYWORDS: Edge detection, Image compression, Image processing, Image registration, Medical imaging, Solids, Image filtering, Optimization (mathematics), Spherical lenses, Image interpolation

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Proceedings Article | 27 March 2009 Paper

Recent improvements in tensor scale computation and its applications to medical imaging

Ziyue Xu, Milan Sonka, Punam Saha

Proceedings Volume 7259, 725939 (2009) https://doi.org/10.1117/12.811360

KEYWORDS: Edge detection, Image compression, Detection and tracking algorithms, Image segmentation, Error analysis, Image registration, Medical imaging, Image filtering, Computed tomography, Spherical lenses

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Proceedings Article | 27 March 2009 Paper

A new method for thresholding and gradient optimization at different tissue interfaces using class uncertainty

Yinxiao Liu, Punam Saha

Proceedings Volume 7259, 72590H (2009) https://doi.org/10.1117/12.811355

KEYWORDS: Tissues, Magnetic resonance imaging, Image segmentation, Error analysis, Interfaces, Bone, Medical imaging, Computed tomography, 3D image processing, Brain

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Proceedings Article | 27 March 2009 Paper

A novel multiscale topo-morphometric approach for separating arteries and veins via pulmonary CT imaging

Punam Saha, Zhiyun Gao, Sara Alford, Milan Sonka, Eric Hoffman

Proceedings Volume 7259, 725910 (2009) https://doi.org/10.1117/12.811339

KEYWORDS: Signal to noise ratio, Veins, X-ray computed tomography, Image segmentation, Image resolution, Arteries, Feature extraction, Computed tomography, Fuzzy logic, 3D image processing

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Proceedings Article | 27 March 2009 Paper

Volumetric topological analysis: a novel method for trabecular bone characterization on the continuum between plates and rods

Punam Saha, Yan Xu, Guoyuan Liang, Hong Duan

Proceedings Volume 7259, 725950 (2009) https://doi.org/10.1117/12.811352

KEYWORDS: Minerals, Visualization, Imaging systems, Magnetic resonance imaging, Image processing, Bone, Biopsy, Computed tomography, Neodymium, Binary data

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Proceedings Article | 28 February 2009 Paper

Quantification of stenosis in coronary artery via CTA using fuzzy distance transform

Yan Xu, Punam Saha, Guangshu Hu, Guoyuan Liang, Yan Yang, Jinzhao Geng

Proceedings Volume 7262, 72620K (2009) https://doi.org/10.1117/12.811361

KEYWORDS: Detection and tracking algorithms, Image segmentation, Heart, Computer simulations, Arteries, Angiography, Algorithm development, Binary data, Fuzzy logic, 3D image processing

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Proceedings Article | 29 March 2007 Paper

Analysis of trabecular bone architectural changes induced by osteoarthritis in rabbit femur using 3D active shape model and digital topology

P. Saha, C. Rajapakse, D. Williams, L. Duong, A. Coimbra

Proceedings Volume 6511, 65110J (2007) https://doi.org/10.1117/12.709064

KEYWORDS: Lithium, Cartilage, Data modeling, 3D modeling, Bone, Shape analysis, Computed tomography, Fuzzy logic, 3D image processing, Animal model studies

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Osteoarthritis (OA) is the most common chronic joint disease, which causes the cartilage between the bone joints to wear away, leading to pain and stiffness. Currently, progression of OA is monitored by measuring joint space width using x-ray or cartilage volume using MRI. However, OA affects all periarticular tissues, including cartilage and bone. It has been shown previously that in animal models of OA, trabecular bone (TB) architecture is particularly affected. Furthermore, relative changes in architecture are dependent on the depth of the TB region with respect to the bone surface and main direction of load on the bone. The purpose of this study was to develop a new method for accurately evaluating 3D architectural changes induced by OA in TB. Determining the TB test domain that represents the same anatomic region across different animals is crucial for studying disease etiology, progression and response to therapy. It also represents a major technical challenge in analyzing architectural changes. Here, we solve this problem using a new active shape model (ASM)-based approach. A new and effective semi-automatic landmark selection approach has been developed for rabbit distal femur surface that can easily be adopted for many other anatomical regions. It has been observed that, on average, a trained operator can complete the user interaction part of landmark specification process in less than 15 minutes for each bone data set. Digital topological analysis and fuzzy distance transform derived parameters are used for quantifying TB architecture. The method has been applied on micro-CT data of excised rabbit femur joints from anterior cruciate ligament transected (ACLT) (n = 6) and sham (n = 9) operated groups collected at two and two-to-eight week post-surgery, respectively. An ASM of the rabbit right distal femur has been generated from the sham group micro-CT data. The results suggest that, in conjunction with ASM, digital topological parameters are suitable for analyzing architectural changes induced by OA.

Proceedings Article | 7 March 2007 Paper

Fuzzy shape-based interpolation

Punam Kumar Saha, Ying Zhuge, Jayaram Udupa

Proceedings Volume 6512, 65123W (2007) https://doi.org/10.1117/12.710279

KEYWORDS: Image segmentation, Image processing, Bone, Medical imaging, Digital imaging, Computed tomography, Skull, Binary data, Fuzzy logic, 3D image processing

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Proceedings Article | 3 March 2007 Paper

Active index model: a unique approach for regional quantitative morphometry in longitudinal and cross-sectional studies

P. Saha, H. Zhang, M. Sonka, G. Christensen, C. Rajapakse

Proceedings Volume 6512, 65121B (2007) https://doi.org/10.1117/12.709022

KEYWORDS: Lithium, Statistical analysis, Magnetic resonance imaging, Image segmentation, Diagnostics, 3D modeling, Image registration, Bone, Shape analysis, Associative arrays

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Proceedings Article | 13 March 2006 Paper

Micro-MRI-based image acquisition and processing system for assessing the response to therapeutic intervention

B. Vasilić, G. Ladinsky, P. Saha, F. Wehrli

Proceedings Volume 6143, 61430W (2006) https://doi.org/10.1117/12.656650

KEYWORDS: Signal to noise ratio, Magnetic resonance imaging, Image segmentation, Image processing, Error analysis, Image registration, Bone, Data acquisition, Image quality, Motion measurement

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Proceedings Article | 13 March 2006 Paper

An intensity standardization-based method for inhomogeneity correction in MRI

Ying Zhuge, Jayaram Udupa, Jiamin Liu, Punam Saha

Proceedings Volume 6143, 614324 (2006) https://doi.org/10.1117/12.653734

KEYWORDS: Data modeling, Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Scanners, Image analysis, Medical imaging, Bismuth, Scene simulation

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Proceedings Article | 29 April 2005 Paper

A new non-parametric method for image intensity inhomogeneity correction using a non-uniform gradient filter and path integrals

Punam Saha

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.596166

KEYWORDS: Visualization, Magnetic resonance imaging, Image segmentation, Image processing, Image acquisition, Image analysis, Imaging devices, Medical imaging, Image filtering, Image classification

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Proceedings Article | 29 April 2005 Paper

Model-based 3D segmentation of the bones of joints in medical images

Jiamin Liu, Jayaram Udupa, Punam Saha, Dewey Odhner, Bruce Hirsch, Sorin Siegler, Scott Simon, Beth Winkelstein

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.595425

KEYWORDS: Magnetic resonance imaging, Image segmentation, 3D modeling, Bone, Medical imaging, Computed tomography, 3D displays, Spine, Binary data, 3D image processing

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Proceedings Article | 29 April 2005 Paper

Cerebrovascular plaque segmentation using object class uncertainty snake in MR images

Bipul Das, Punam Saha, Ronald Wolf, Hee Kwon Song, Alexander Wright, Felix Wehrli

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.596150

KEYWORDS: Image processing algorithms and systems, Neck, Data modeling, Blood, Magnetic resonance imaging, Image segmentation, Arteries, In vivo imaging, Radiology, Fuzzy logic

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Atherosclerotic cerebrovascular disease leads to formation of lipid-laden plaques that can form emboli when ruptured causing blockage to cerebral vessels. The clinical manifestation of this event sequence is stroke; a leading cause of disability and death. In vivo MR imaging provides detailed image of vascular architecture for the carotid artery making it suitable for analysis of morphological features. Assessing the status of carotid arteries that supplies blood to the brain is of primary interest to such investigations. Reproducible quantification of carotid artery dimensions in MR images is essential for plaque analysis. Manual segmentation being the only method presently makes it time consuming and sensitive to inter and intra observer variability. This paper presents a deformable model for lumen and vessel wall segmentation of carotid artery from MR images. The major challenges of carotid artery segmentation are (a) low signal-to-noise ratio, (b) background intensity inhomogeneity and (c) indistinct inner and/or outer vessel wall. We propose a new, effective object-class uncertainty based deformable model with additional features tailored toward this specific application. Object-class uncertainty optimally utilizes MR intensity characteristics of various anatomic entities that enable the snake to avert leakage through fuzzy boundaries. To strengthen the deformable model for this application, some other properties are attributed to it in the form of (1) fully arc-based deformation using a Gaussian model to maximally exploit vessel wall smoothness, (2) construction of a forbidden region for outer-wall segmentation to reduce interferences by prominent lumen features and (3) arc-based landmark for efficient user interaction. The algorithm has been tested upon T1- and PD-weighted images. Measures of lumen area and vessel wall area are computed from segmented data of 10 patient MR images and their accuracy and reproducibility are examined. These results correspond exceptionally well with manual segmentation completed by radiology experts. Reproducibility of the proposed method is estimated for both intra- and inter-operator studies.

Proceedings Article | 14 April 2005 Paper

Study of trabecular bone microstructure using spatial autocorrelation analysis

Michael Wald, Branimir Vasilic, Punam Saha, Felix Wehrli

Proceedings Volume 5746, (2005) https://doi.org/10.1117/12.596133

KEYWORDS: Signal to noise ratio, Magnetic resonance imaging, Image segmentation, Fourier transforms, Image resolution, Bone, 3D metrology, In vivo imaging, 3D image processing, Anisotropy

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Proceedings Article | 14 April 2005 Paper

Predicting mechanical competence of trabecular bone using 3D tensor-scale-based parameters

Punam Saha, Michael Wald, Alex Radin, Felix Wehrli

Proceedings Volume 5746, (2005) https://doi.org/10.1117/12.596161

KEYWORDS: Signal to noise ratio, Statistical analysis, Image processing, Bone, Computer vision technology, Machine vision, In vivo imaging, Spatial resolution, 3D image processing, Anisotropy

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Proceedings Article | 12 May 2004 Paper

Tensor-scale-based diffusive filtering of medical images

Punam Saha

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.535676

KEYWORDS: Signal to noise ratio, Anisotropic filtering, Image processing, Digital filtering, Diffusion, Medical imaging, Image filtering, Electronic filtering, Anisotropic diffusion, Anisotropy

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Proceedings Article | 12 May 2004 Paper

Object class uncertainty induced snake with applications to medical image segmentation

Bipul Das, Punam Saha, Felix Wehrli

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.535547

KEYWORDS: Visualization, Magnetic resonance imaging, Image segmentation, Image processing, 3D modeling, Medical imaging, Medical imaging applications, Binary data, Fuzzy logic, Brain

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Proceedings Article | 30 April 2004 Paper

3D stress MRI for studying the functional pathologies of the ankle complex

Jayaram Udupa, Sorin Siegler, Bruce Hirsch, Stacie Ringleb, Enyi Okereke, Neil Roach, Carl Imhauser, Dewey Odhner, Jiamin Liu, Punam Saha

Proceedings Volume 5369, (2004) https://doi.org/10.1117/12.536433

KEYWORDS: Magnetic resonance imaging, Image processing, Pathology, Kinematics, Image analysis, Bone, 3D metrology, Atomic layer deposition, In vitro testing, 3D image processing

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Proceedings Article | 30 April 2004 Paper

In vivo assessment of trabecular bone architecture via three-dimensional tensor scale

Punam Saha, Felix Wehrli

Proceedings Volume 5369, (2004) https://doi.org/10.1117/12.535352

KEYWORDS: Magnetic resonance imaging, Image segmentation, Image processing, Bone, Medical imaging, Image classification, In vivo imaging, Binary data, 3D image processing, Anisotropy

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Proceedings Article | 15 May 2003 Paper

Tensor scale-based image registration

Punam Saha, Hui Zhang, Jayaram Udupa, James Gee

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.481433

KEYWORDS: Principal component analysis, Image compression, Magnetic resonance imaging, Image segmentation, 3D modeling, Image registration, Medical imaging, Neuroimaging, Anisotropy, Brain

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Proceedings Article | 15 May 2003 Paper

Model-based 3D segmentation of the bones of the ankle and subtalar joints in MR images

Jiamin Liu, Jayaram Udupa, Punam Saha, Dewey Odhner, Bruce Hirsch, Sorin Siegler

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.483574

KEYWORDS: Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Kinematics, 3D modeling, Bone, Medical imaging, Binary data, 3D image processing

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Proceedings Article | 15 May 2003 Paper

Novel theory and methods for tensor scale: a local morphometric parameter

Punam Saha

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.480645

KEYWORDS: Magnetic resonance imaging, Image segmentation, Image processing, Image resolution, Image analysis, Digital imaging, Neuroimaging, Spherical lenses, Anisotropy, Brain

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Proceedings Article | 15 May 2003 Paper

Tensor scale-based fuzzy connectedness image segmentation

Punam Saha, Jayaram Udupa

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.481882

KEYWORDS: Visualization, Magnetic resonance imaging, Image segmentation, Image processing, Medical imaging, Machine vision, Spherical lenses, Fuzzy logic, Anisotropy, Brain

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Proceedings Article | 15 May 2003 Paper

Quantification of trabecular bone anisotropy by means of tensor scale

Punam Saha, Felix Wehrli

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.481884

KEYWORDS: Image compression, Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Image resolution, Bone, In vivo imaging, 3D image processing, Anisotropy

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Proceedings Article | 17 May 2002 Paper

Volume rendering in the presence of partial volume effects

Andre Souza, Jayaram Udupa, Punam Saha

Proceedings Volume 4681, (2002) https://doi.org/10.1117/12.466974

KEYWORDS: X-ray computed tomography, Tissues, Image segmentation, Skin, X-rays, Bone, Volume rendering, Frequency modulation, Fermium, Computed tomography

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