Search Results - "Veni, Gopalkrishna"

The DTI Challenge: Toward Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery by Pujol, Sonia, Wells, William, Pierpaoli, Carlo, Brun, Caroline, Gee, James, Cheng, Guang, Vemuri, Baba, Commowick, Olivier, Prima, Sylvain, Stamm, Aymeric, Goubran, Maged, Khan, Ali, Peters, Terry, Neher, Peter, Maier-Hein, Klaus H., Shi, Yundi, Tristan-Vega, Antonio, Veni, Gopalkrishna, Whitaker, Ross, Styner, Martin, Westin, Carl-Fredrik, Gouttard, Sylvain, Norton, Isaiah, Chauvin, Laurent, Mamata, Hatsuho, Gerig, Guido, Nabavi, Arya, Golby, Alexandra, Kikinis, Ron

“…ABSTRACT BACKGROUND AND PURPOSE Diffusion tensor imaging (DTI) tractography reconstruction of white matter pathways can help guide brain tumor resection…”
Get full text

Microcalcification detection based on wavelet domain hidden Markov tree model: Study for inclusion to computer aided diagnostic prompting system by Regentova, Emma, Zhang, Lei, Zheng, Jun, Veni, Gopalkrishna

“…In this paper we investigate the performance of statistical modeling of digital mammograms by means of wavelet domain hidden Markov trees for its inclusion to…”
Get full text

ShapeCut: Bayesian surface estimation using shape-driven graph by Veni, Gopalkrishna, Elhabian, Shireen Y., Whitaker, Ross T.

“…•Developed surface-based image segmentation scheme based on generative image model.•Used parametric shape model and graph-cuts to build global and local shape…”
Get full text

Echocardiography segmentation based on a shape-guided deformable model driven by a fully convolutional network prior by Veni, Gopalkrishna, Moradi, Mehdi, Bulu, Hakan, Narayan, Girish, Syeda-Mahmood, Tanveer

“…Advances in deep learning have yielded simplified solutions in many challenging medical imaging problems. Despite their capability, these learning approaches…”
Get full text

Detecting anomalies from echocardiography using multi-view regression of clinical measurements by Lu, Allen, Dehghan, Ehsan, Veni, Gopalkrishna, Moradi, Mehdi, Syeda-Mahmood, Tanveer

“…Automated methods for detection of abnormalities in echocardiography are valuable for screening and routing patients with various cardiovascular diseases…”
Get full text

Surface-based image segmentation using application-specific priors by Veni, Gopalkrishna

“…Image segmentation entails the partitioning of an image domain, usually two or three dimensions, so that each partition or segment has some meaning that is…”
Get full text

A Bayesian formulation of graph-cut surface estimation with global shape priors by Veni, Gopalkrishna, Elhabian, Shireen Y., Whitaker, Ross T.

“…In this paper, we propose a formulation of graph-cut segmentation that relies on a generative image model by incorporating both local and global shape priors…”
Get full text

Proper ordered meshing of complex shapes and optimal graph cuts applied to atrial-wall segmentation from DE-MRI by Veni, Gopalkrishna, Zhisong Fu, Awate, Suyash P., Whitaker, Ross T.

“…Segmentation of the left atrium wall from delayed enhancement MRI is challenging because of inconsistent contrast combined with noise and high variation in…”
Get full text

The DTI Challenge: Towards Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery by Pujol, Sonia, Wells, William, Pierpaoli, Carlo, Brun, Caroline, Gee, James, Cheng, Guang, Vemuri, Baba, Commowick, Olivier, Prima, Sylvain, Stamm, Aymeric, Goubran, Maged, Khan, Ali, Peters, Terry, Neher, Peter, Maier-Hein, Klaus H., Shi, Yundi, Tristan-Vega, Antonio, Veni, Gopalkrishna, Whitaker, Ross, Styner, Martin, Westin, Carl-Fredrik, Gouttard, Sylvain, Norton, Isaiah, Chauvin, Laurent, Mamata, Hatsuho, Gerig, Guido, Nabavi, Arya, Golby, Alexandra, Kikinis, Ron

Get full text

Microcalcification detection based on wavelet domain hiddenMarkov tree model: Study for inclusion to computer aideddiagnostic prompting system by Regentova, Emma, Zhang, Lei, Zheng, Jun, Veni, Gopalkrishna

“…In this paper we investigate the performance of statistical modeling of digital mammograms by means of wavelet domain hidden Markov trees for its inclusion to…”
Get full text

Bayesian segmentation of atrium wall using globally-optimal graph cuts on 3D meshes by Veni, Gopalkrishna, Fu, Zhisong, Awate, Suyash P, Whitaker, Ross T

“…Efficient segmentation of the left atrium (LA) wall from delayed enhancement MRI is challenging due to inconsistent contrast, combined with noise, and high…”
Get more information

Illegible Text to Readable Text: An Image-to-Image Transformation using Conditional Sliced Wasserstein Adversarial Networks by Karimi, Mostafa, Veni, Gopalkrishna, Yu, Yen-Yun

“…Automatic text recognition from ancient handwritten record images is an important problem in the genealogy domain. However, critical challenges such as varying…”
Get full text

Illegible Text to Readable Text: An Image-to-Image Transformation using Conditional Sliced Wasserstein Adversarial Networks by Karimi, Mostafa, Veni, Gopalkrishna, Yu, Yen-Yun

“…Automatic text recognition from ancient handwritten record images is an important problem in the genealogy domain. However, critical challenges such as varying…”
Get full text

Quantitative analysis of cytokine-induced vascular toxicity and vascular leak in the mouse brain by Irwan, Yetty Y., Feng, Yi, Gach, H. Michael, Symanowski, James T., McGregor, John R., Veni, Gopalkrishna, Schabel, Matthias, Samlowski, Wolfram E.

“…A storm of inflammatory cytokines is released during treatment with pro-inflammatory cytokines, such as interleukin-2 (IL-2), closely approximating changes…”
Get full text

Detecting microcalcification clusters in digital mammograms: Study for inclusion into computer aided diagnostic prompting system by Veni, Gopalkrishna

“…Among signs of breast cancer encountered in digital mammograms radiologists point to microcalcification clusters (MCCs). Their detection is a challenging…”
Get full text

Detecting Microcalcifications in Digital Mammograms using Wavelet Domain Hidden Markov Tree Model by Regentova, E., Zhang, L., Zheng, J., Veni, G.

“…In this paper we investigate the performance of statistical modeling of digital mammograms by means of wavelet domain hidden Markov tree model (WHMT) for its…”
Get full text