Search Results - "Varghese, Bino A"

Texture Analysis of Imaging: What Radiologists Need to Know by Varghese, Bino A, Cen, Steven Y, Hwang, Darryl H, Duddalwar, Vinay A

“…Radiologic texture is the variation in image intensities within an image and is an important part of radiomics. The objective of this article is to discuss…”
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Differentiation of Predominantly Solid Enhancing Lipid-Poor Renal Cell Masses by Use of Contrast-Enhanced CT: Evaluating the Role of Texture in Tumor Subtyping by Varghese, Bino A, Chen, Frank, Hwang, Darryl H, Cen, Steven Y, Desai, Bhushan, Gill, Inderbir S, Duddalwar, Vinay A

“…The purpose of this study was to assess the accuracy of a panel of texture features extracted from clinical CT in differentiating benign from malignant solid…”
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Reliability of CT‐based texture features: Phantom study by Varghese, Bino A., Hwang, Darryl, Cen, Steven Y., Levy, Joshua, Liu, Derek, Lau, Christopher, Rivas, Marielena, Desai, Bhushan, Goodenough, David J., Duddalwar, Vinay A.

“…Objective To determine the intra‐, inter‐ and test‐retest variability of CT‐based texture analysis (CTTA) metrics. Materials and methods In this study, we…”
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Artificial intelligence and machine learning applications for the imaging of bone and soft tissue tumors by Sabeghi, Paniz, Kinkar, Ketki K, Castaneda, Gloria Del Rosario, Eibschutz, Liesl S, Fields, Brandon K K, Varghese, Bino A, Patel, Dakshesh B, Gholamrezanezhad, Ali

“…Recent advancements in artificial intelligence (AI) and machine learning offer numerous opportunities in musculoskeletal radiology to potentially bolster…”
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Spatial assessments in texture analysis: what the radiologist needs to know by Varghese, Bino A, Fields, Brandon K K, Hwang, Darryl H, Duddalwar, Vinay A, Matcuk, Jr, George R, Cen, Steven Y

“…To date, studies investigating radiomics-based predictive models have tended to err on the side of data-driven or exploratory analysis of many thousands of…”
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Empowering breast cancer diagnosis and radiology practice: advances in artificial intelligence for contrast-enhanced mammography by Kinkar, Ketki K, Fields, Brandon K K, Yamashita, Mary W, Varghese, Bino A

“…Artificial intelligence (AI) applications in breast imaging span a wide range of tasks including decision support, risk assessment, patient management, quality…”
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Radiomics in Pulmonary Lesion Imaging by Hassani, Cameron, Varghese, Bino A, Nieva, Jorge, Duddalwar, Vinay

“…Diagnostic imaging has traditionally relied on a limited set of qualitative imaging characteristics for the diagnosis and management of lung cancer…”
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Liver‐Directed Human Amniotic Epithelial Cell Transplantation Improves Systemic Disease Phenotype in Hurler Syndrome Mouse Model by Rodriguez, Natalie S., Yanuaria, Lisa, Parducho, Kevin Murphy R., Garcia, Irving M., Varghese, Bino A., Grubbs, Brendan H., Miki, Toshio

“…Mucopolysaccharidosis type 1 (MPS1) is an inherited lysosomal storage disorder caused by a deficiency in the glycosaminoglycan (GAG)‐degrading enzyme…”
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Myocardial Radiomics in Cardiac MRI by Hassani, Cameron, Saremi, Farhood, Varghese, Bino A, Duddalwar, Vinay

“…The purpose of this article is to review the nascent field of radiomics in cardiac MRI. Cardiac MRI produces a large number of images in a fairly inefficient…”
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A Decision-Support Tool for Renal Mass Classification by Kunapuli, Gautam, Varghese, Bino A., Ganapathy, Priya, Desai, Bhushan, Cen, Steven, Aron, Manju, Gill, Inderbir, Duddalwar, Vinay

“…We investigate the viability of statistical relational machine learning algorithms for the task of identifying malignancy of renal masses using radiomics-based…”
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CT-based radiomics stratification of tumor grade and TNM stage of clear cell renal cell carcinoma by Demirjian, Natalie L., Varghese, Bino A., Cen, Steven Y., Hwang, Darryl H., Aron, Manju, Siddiqui, Imran, Fields, Brandon K. K., Lei, Xiaomeng, Yap, Felix Y., Rivas, Marielena, Reddy, Sharath S., Zahoor, Haris, Liu, Derek H., Desai, Mihir, Rhie, Suhn K., Gill, Inderbir S., Duddalwar, Vinay

“…Objectives To evaluate the utility of CT-based radiomics signatures in discriminating low-grade (grades 1–2) clear cell renal cell carcinomas (ccRCC) from…”
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Whole-tumor 3D volumetric MRI-based radiomics approach for distinguishing between benign and malignant soft tissue tumors by Fields, Brandon K. K., Demirjian, Natalie L., Hwang, Darryl H., Varghese, Bino A., Cen, Steven Y., Lei, Xiaomeng, Desai, Bhushan, Duddalwar, Vinay, Matcuk, George R.

“…Objectives Our purpose was to differentiate between malignant from benign soft tissue neoplasms using a combination of MRI-based radiomics metrics and machine…”
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Shape and texture-based radiomics signature on CT effectively discriminates benign from malignant renal masses by Yap, Felix Y., Varghese, Bino A., Cen, Steven Y., Hwang, Darryl H., Lei, Xiaomeng, Desai, Bhushan, Lau, Christopher, Yang, Lindsay L., Fullenkamp, Austin J., Hajian, Simin, Rivas, Marielena, Gupta, Megha Nayyar, Quinn, Brian D., Aron, Manju, Desai, Mihir M., Aron, Monish, Oberai, Assad A., Gill, Inderbir S., Duddalwar, Vinay A.

“…Objectives Using a radiomics framework to quantitatively analyze tumor shape and texture features in three dimensions, we tested its ability to objectively and…”
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Predicting Soft Tissue Sarcoma Response to Neoadjuvant Chemotherapy Using an MRI-Based Delta-Radiomics Approach by Fields, Brandon K. K., Demirjian, Natalie L., Cen, Steven Y., Varghese, Bino A., Hwang, Darryl H., Lei, Xiaomeng, Desai, Bhushan, Duddalwar, Vinay, Matcuk, George R.

“…Objectives To evaluate the performance of machine learning–augmented MRI-based radiomics models for predicting response to neoadjuvant chemotherapy (NAC) in…”
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Identification of robust and reproducible CT‐texture metrics using a customized 3D‐printed texture phantom by Varghese, Bino A., Hwang, Darryl, Cen, Steven Y., Lei, Xiaomeng, Levy, Joshua, Desai, Bhushan, Goodenough, David J., Duddalwar, Vinay A.

“…Objective The objective of this study was to evaluate the robustness and reproducibility of computed tomography‐based texture analysis (CTTA) metrics extracted…”
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Quantitative Contour Analysis as an Image-based Discriminator Between Benign and Malignant Renal Tumors by Yap, Felix Y., Hwang, Darryl H., Cen, Steven Y., Varghese, Bino A., Desai, Bhushan, Quinn, Brian D., Gupta, Megha Nayyar, Rajarubendra, Nieroshan, Desai, Mihir M., Aron, Manju, Liang, Gangning, Aron, Monish, Gill, Inderbir S., Duddalwar, Vinay A.

“…To investigate whether morphologic analysis can differentiate between benign and malignant renal tumors on clinically acquired imaging. Between 2009 and 2014,…”
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Radiogenomic Associations Clear Cell Renal Cell Carcinoma: An Exploratory Study by Liu, Derek H, Dani, Komal A, Reddy, Sharath S, Lei, Xiaomeng, Demirjian, Natalie L, Hwang, Darryl H, Varghese, Bino A, Rhie, Suhn Kyong, Yap, Felix Y, Quinn, David I, Siddiqi, Imran, Aron, Manju, Vaishampayan, Ulka, Zahoor, Haris, Cen, Steven Y, Gill, Inderbir S, Duddalwar, Vinay A

“…This study investigates how quantitative texture analysis can be used to non-invasively identify novel radiogenomic correlations with clear cell renal cell…”
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Differentiating solid, non-macroscopic fat containing, enhancing renal masses using fast Fourier transform analysis of multiphase CT by Varghese, Bino A, Chen, Frank, Hwang, Darryl H, Cen, Steven Y, Gill, Inderbir S, Duddalwar, Vinay A

“…To test the feasibility of two-dimensional fast Fourier transforms (FFT)-based imaging metrics in differentiating solid, non-macroscopic fat containing,…”
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Juxtatumoral perinephric fat analysis in clear cell renal cell carcinoma by Gill, Tania S., Varghese, Bino A., Hwang, Darryl H., Cen, Steven Y., Aron, Manju, Aron, Monish, Duddalwar, Vinay A.

“…Purpose The purpose of the study was to evaluate the feasibility of using contrast-enhanced computed tomography (CECT)-based texture analysis (CTTA) metrics to…”
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Characterizing breast masses using an integrative framework of machine learning and CEUS-based radiomics by Varghese, Bino A., Lee, Sandy, Cen, Steven, Talebi, Amir, Mohd, Passant, Stahl, Daniel, Perkins, Melissa, Desai, Bhushan, Duddalwar, Vinay A., Larsen, Linda H.

“…Aims We evaluated the performance of contrast-enhanced ultrasound (CEUS) based on radiomics analysis to distinguish benign from malignant breast masses…”
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