Despina Kontos

发表

An MCMC Feature Selection Technique for Characterizing and Classifying Spatial Region Data

Qiang Wang, Vasileios Megalooikonomou, Despina Kontos, 2004, SSPR/SPR.

Classification and Mining of Brain Image Data Using Adaptive Recursive Partitioning Methods: Application to Alzheimer Disease and Brain Activation Patterns

Fillia Makedon, Andrew J. Saykin, Zoran Obradovic, 2003 .

Automatic breast segmentation in digital mammography using a convolutional neural network

Aimilia Gastounioti, Despina Kontos, Omid Haji Maghsoudi, 2020, Other Conferences.

Assessment of CT image reconstruction parameters on radiomic features in a lung cancer screening cohort: the PROSPR study

Peter B. Noël, Despina Kontos, Lauren Pantalone, 2020, Medical Imaging.

Pattern analysis for regions of interest in spatial data with applications to medical images

Vasileios Megalooikonomou, Despina Kontos, 2006 .

Classification of galactograms using fractal properties of the breast ductal network

Vasileios Megalooikonomou, Andrew D. A. Maidment, Predrag R. Bakic, 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

Computationally Intelligent Methods for Mining 3D Medical Images

Fillia Makedon, Vasileios Megalooikonomou, Despina Kontos, 2004, SETN.

Pharmacokinetic Tumor Heterogeneity as a Prognostic Biomarker for Classifying Breast Cancer Recurrence Risk

Michael D. Feldman, Mark Rosen, Ahmed Bilal Ashraf, 2015, IEEE Transactions on Biomedical Engineering.

Fast and effective characterization for classification and similarity searches of 2D and 3D spatial region data

Vasileios Megalooikonomou, Despina Kontos, 2005, Pattern Recognit..

Deep-LIBRA: Artificial intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment pdf

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2020, ArXiv.

Intensity standardization in breast MR images improves tissue quantification

Jayaram K. Udupa, Despina Kontos, Susan P. Weinstein, 2013, Medical Imaging.

Deformable image registration as a tool to improve survival prediction after neoadjuvant chemotherapy for breast cancer: results from the ACRIN 6657/I-SPY-1 trial

Christos Davatzikos, Despina Kontos, Susan P. Weinstein, 2018, Medical Imaging.

Comparison of breast percent density estimation from raw versus processed digital mammograms

Emily F. Conant, Despina Kontos, Diane Li, 2011, Medical Imaging.

Fully automated chest wall line segmentation in breast MRI by using context information

Mitchell D. Schnall, Shandong Wu, Emily F. Conant, 2012, Medical Imaging.

A statistical approach for selecting discriminative features of spatial regions of interest

Vasileios Megalooikonomou, Despina Kontos, Vasileios J. Sobel, 2007, Intell. Data Anal..

Application of computer-extracted breast tissue texture features in predicting false-positive recalls from screening mammography

Emily F. Conant, Jinbo Chen, Despina Kontos, 2014, Medical Imaging.

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method.

Shandong Wu, Despina Kontos, Susan P Weinstein, 2013, Medical physics.

Calculation of radiomic features to validate the textural realism of physical anthropomorphic phantoms for digital mammography

Andrew D. A. Maidment, Predrag R. Bakic, Bruno Barufaldi, 2020, Other Conferences.

A 3D image analysis tool for SPECT imaging

Qiang Wang, Vasileios Megalooikonomou, Despina Kontos, 2005, SPIE Medical Imaging.

Breast density and parenchymal texture measures as potential risk factors for estrogen-receptor positive breast cancer

Emily F. Conant, Despina Kontos, Brad M. Keller, 2014, Medical Imaging.

Adaptive Multi-cluster Fuzzy C-Means Segmentation of Breast Parenchymal Tissue in Digital Mammography

Yan Wang, James C. Gee, Yuanjie Zheng, 2011, MICCAI.

Correlation between Topological Descriptors of the Breast Ductal Network from Clinical Galactograms and Texture Features of Corresponding Mammograms

James C. Gee, Yuanjie Zheng, Vasileios Megalooikonomou, 2014, Digital Mammography / IWDM.

Three-Dimensional Whole Breast Segmentation in Sagittal and Axial Breast MRI With Dense Depth Field Modeling and Localized Self-Adaptation for Chest-Wall Line Detection

Dong Wei, Despina Kontos, Meng-Kang Hsieh, 2019, IEEE Transactions on Biomedical Engineering.

O-Net: An Overall Convolutional Network for Segmentation Tasks

Christos Davatzikos, Spyridon Bakas, Aimilia Gastounioti, 2020, MLMI@MICCAI.

Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices

Yuanjie Zheng, Despina Kontos, Shonket Ray, 2015, Journal of medical imaging.

Breast percent density estimation from 3D reconstructed digital breast tomosynthesis images

Ann-Katherine Carton, Andrew D. A. Maidment, Predrag R. Bakic, 2008, SPIE Medical Imaging.

A Phantom Study for Assessing the Effect of Different Digital Detectors on Mammographic Texture Features

Yan Wang, James C. Gee, Yuanjie Zheng, 2012, Digital Mammography / IWDM.

Heterogeneity Wavelet Kinetics from DCE-MRI for Classifying Gene Expression Based Breast Cancer Recurrence Risk

Michael D. Feldman, Mark Rosen, Ahmed Bilal Ashraf, 2013, MICCAI.

Analyzing Tree-Like Structures in Biomedical Images Based on Texture and Branching: An Application to Breast Imaging

Vasileios Megalooikonomou, Andrew D. A. Maidment, Predrag R. Bakic, 2008, Digital Mammography / IWDM.

Segmentation of anatomical branching structures based on texture features and conditional random field

Vasileios Megalooikonomou, Haibin Ling, Predrag R. Bakic, 2012, Medical Imaging.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

Christos Davatzikos, Ragini Verma, Spyridon Bakas, 2018, Journal of medical imaging.

Application of time series techniques to data mining and analysis of spatial patterns in 3D images

Qiang Wang, Vasileios Megalooikonomou, Guo Li, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging.

Emily F. Conant, Despina Kontos, Elizabeth S. McDonald, 2016, Radiology.

Associations between mammographic phenotypes and histopathologic features in ductal carcinoma in situ

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2019, Medical Imaging.

Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2017, Medical Imaging.

Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.

Aimilia Gastounioti, Despina Kontos, Meng-Kang Hsieh, 2018, Academic radiology.

Fast and effective characterization of 3D region data

Haimonti Dutta, Vasileios Megalooikonomou, Despina Kontos, 2002, Proceedings. International Conference on Image Processing.

Analysis of texture patterns in medical images with an application to breast imaging

Vasileios Megalooikonomou, Predrag R. Bakic, Jingjing Zhang, 2007, SPIE Medical Imaging.

Automated chest wall line detection for whole-breast segmentation in sagittal breast MR images.

Shandong Wu, Despina Kontos, Mitchell D Schnall, 2013, Medical physics.

Texture feature standardization in digital mammography for improving generalizability across devices

Yan Wang, James C. Gee, Yuanjie Zheng, 2013, Medical Imaging.

Volumetric versus area-based density assessment: comparisons using automated quantitative measurements from a large screening cohort

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2018, Medical Imaging.

Extraction of Discriminative Functional MRI Activation Patterns and an Application to Alzheimer's Disease

Fillia Makedon, Andrew J. Saykin, Zoran Obradovic, 2004, MICCAI.

Special Section Guest Editorial: Radiomics and Deep Learning

Maryellen Giger, Despina Kontos, Ronald M Summers, 2017, Journal of medical imaging.

Atlas-Based Probabilistic Fibroglandular Tissue Segmentation in Breast MRI

Shandong Wu, Despina Kontos, Susan Weinstein, 2012, MICCAI.

Comparison of Methods for Classification of Breast Ductal Branching Patterns

Vasileios Megalooikonomou, Andrew D. A. Maidment, Predrag R. Bakic, 2006, Digital Mammography / IWDM.

A fully-automated software pipeline for integrating breast density and parenchymal texture analysis for digital mammograms: parameter optimization in a case-control breast cancer risk assessment study

Yan Wang, James C. Gee, Yuanjie Zheng, 2013, Medical Imaging.

Validation of the textural realism of a 3D anthropomorphic phantom for digital breast tomosynthesis

Yifan Hu, Andrew D. A. Maidment, Jinbo Chen, 2018, Other Conferences.

Fast and effective characterization of 3D region of interest in medical image data

Vasileios Megalooikonomou, Despina Kontos, 2004, SPIE Medical Imaging.

Analysis of percent density estimates from digital breast tomosynthesis projection images

Andrew D. A. Maidment, Martin J. Yaffe, Cuiping Zhang, 2007, SPIE Medical Imaging.

FFDM image quality assessment using computerized image texture analysis

Ann-Katherine Carton, Andrew D. A. Maidment, Despina Kontos, 2010, Medical Imaging.

Fully-automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI by integrating a continuous max-flow model and a likelihood atlas

Shandong Wu, Emily F. Conant, Despina Kontos, 2013, Medical Imaging.

Automatic segmentation of breast carcinomas from DCE-MRI using a Statistical Learning Algorithm

Kilian M. Pohl, Ferenc A. Jolesz, Jagadeesan Jayender, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

Model-based estimation of breast percent density in raw and processed full-field digital mammography images from image-acquisition physics and patient-image characteristics

Emily F. Conant, Despina Kontos, Brad M. Keller, 2012, Medical Imaging.

Precision diagnostics based on machine learning-derived imaging signatures.

Christos Davatzikos, Spyridon Bakas, Mohamad Habes, 2019, Magnetic resonance imaging.

Texture in digital breast tomosynthesis: a comparison between mammographic and tomographic characterization of parenchymal properties

Andrew D. A. Maidment, Predrag R. Bakic, Despina Kontos, 2008, SPIE Medical Imaging.

Mammographic Parenchymal Texture Analysis for Estrogen-Receptor Subtype Specific Breast Cancer Risk Estimation

Mads Nielsen, Emily F. Conant, Despina Kontos, 2012, Digital Mammography / IWDM.

Fully-Automated Fibroglandular Tissue Segmentation in Breast MRI

Shandong Wu, Emily F. Conant, Despina Kontos, 2012, Digital Mammography / IWDM.

Automatic segmentation of fibroglandular tissue in breast MRI using anatomy-driven three-dimensional spatial context

Despina Kontos, Lauren Pantalone, Meng-Kang Hsieh, 2018, Medical Imaging.

Digital Breast Tomosynthesis Parenchymal Texture Analysis for Breast Cancer Risk Estimation: A Preliminary Study

Andrew D. A. Maidment, Predrag R. Bakic, Emily F. Conant, 2008, Digital Mammography / IWDM.

A Multichannel Markov Random Field Approach for Automated Segmentation of Breast Cancer Tumor in DCE-MRI Data Using Kinetic Observation Model

Michael D. Feldman, Mark Rosen, Ahmed Bilal Ashraf, 2011, MICCAI.

Parameter optimization of parenchymal texture analysis for prediction of false-positive recalls from screening mammography

Emily F. Conant, Jinbo Chen, Despina Kontos, 2016, SPIE Medical Imaging.

Preliminary evaluation of a fully automated quantitative framework for characterizing general breast tissue histology via color histogram and color texture analysis

Michael D. Feldman, Aimilia Gastounioti, Despina Kontos, 2016, SPIE Medical Imaging.

Utilizing Domain Knowledge in Developing Robust Neural Network Models for Peptide-Allele Binding Prediction

Vasileios Megalooikonomou, Pedro Cano, Despina Kontos, 2005, CIBCB.

A tool for handling uncertainty in segmenting regions of interest in medical images

Qiang Wang, Vasileios Megalooikonomou, Despina Kontos, 2006, Int. J. Intell. Syst. Technol. Appl..

Three-dimensional whole breast segmentation in sagittal MR images with dense depth field modeling and localized self-adaptation

Dong Wei, Mitchell D. Schnall, Despina Kontos, 2017, Medical Imaging.

Testing realism of software breast phantoms: texture analysis of synthetic mammograms

James C. Gee, Yuanjie Zheng, Andrew D. A. Maidment, 2013, Medical Imaging.

An adaptive partitioning approach for mining discriminant regions in 3D image data

Zoran Obradovic, Aleksandar Lazarevic, Dragoljub Pokrajac, 2008, Journal of Intelligent Information Systems.

Correlative hierarchical clustering-based low-rank dimensionality reduction of radiomics-driven phenotype in non-small cell lung cancer

Bardia Yousefi, Despina Kontos, Nariman Jahani, 2019, Medical Imaging.

Analysis of parenchymal texture properties in breast tomosynthesis images

Andrew D. A. Maidment, Predrag R. Bakic, Despina Kontos, 2007, SPIE Medical Imaging.

Breast Cancer Risk Prediction via Area and Volumetric Estimates of Breast Density

Emily F. Conant, Despina Kontos, Brad M. Keller, 2012, Digital Mammography / IWDM.

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

Michael D. Feldman, Mark Rosen, Ahmed Bilal Ashraf, 2014, Medical Imaging.

Comparison of Breast Percent Density Estimated from Digital Mammograms and Central Reconstructed Tomosynthesis Slice Images

Andrew D. A. Maidment, Predrag R. Bakic, Despina Kontos, 2008, Digital Mammography / IWDM.

Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women

Andrew D. A. Maidment, Emily F. Conant, Despina Kontos, 2011, Medical Imaging.

A Comparative Study of the Inter-reader Variability of Breast Percent Density Estimation in Digital Mammography: Potential Effect of Reader's Training and Clinical Experience

Ann-Katherine Carton, Andrew D. A. Maidment, Cuiping Zhang, 2010, Digital Mammography / IWDM.

A superpixel-based framework for automatic tumor segmentation on breast DCE-MRI

Bilwaj Gaonkar, Christos Davatzikos, Jia Wu, 2015, Medical Imaging.

Segmentation of anatomical branching structures based on texture features and graph cut

Vasileios Megalooikonomou, Haibin Ling, Predrag R. Bakic, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Evaluating the Effect of Tomosynthesis Acquisition Parameters on Image Texture: A Study Based on an Anthropomorphic Breast Tissue Software Model

Andrew D. A. Maidment, Cuiping Zhang, Predrag R. Bakic, 2008, Digital Mammography / IWDM.

A Representation and Classification Scheme for Tree-Like Structures in Medical Images: Analyzing the Branching Pattern of Ductal Trees in X-ray Galactograms

Vasileios Megalooikonomou, Andrew D. A. Maidment, Predrag R. Bakic, 2009, IEEE Transactions on Medical Imaging.

Morphometric analysis of brain images with reduced number of statistical tests: A study on the gender-related differentiation of the corpus callosum

James C. Gee, Vasileios Megalooikonomou, Despina Kontos, 2009, Artif. Intell. Medicine.

Breast tissue classification in digital breast tomosynthesis images using texture features: a feasibility study

Andrew D. A. Maidment, Predrag R. Bakic, Despina Kontos, 2009, Medical Imaging.

The National Cancer Institute's Informatics Technology for Cancer Research Program: Building a Community of Practice in Cancer Informatics

Juli D. Klemm, Despina Kontos, Ian Holmes, 2019, AMIA.

Robust radiomic feature selection in digital mammography: understanding the effect of imaging acquisition physics using phantom and clinical data analysis

Andrew D. A. Maidment, Emily F. Conant, Karla Kerlikowske, 2020, Medical Imaging.

Reducing the computational cost for statistical medical image analysis: an MRI study on the sexual morphological differentiation of the corpus callosum

James C. Gee, Vasileios Megalooikonomou, Despina Kontos, 2005, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05).

A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: results from a high-risk population

Andrew D. A. Maidment, Predrag R. Bakic, Emily F. Conant, 2010, Medical Imaging.

Fully Automatic Quantification of Fibroglandular Tissue and Background Parenchymal Enhancement with Accurate Implementation for Axial and Sagittal Breast MRI Protocols.

Despina Kontos, Lauren Pantalone, Eric Cohen, 2020, Medical physics.

Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration

Christos Davatzikos, Jia Wu, Mark Rosen, 2015, Medical Imaging.

Subjective Probability

Zoran Obradovic, Aleksandar Lazarevic, Dragoljub Pokrajac, 1994 .

Parenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment.

Yuanjie Zheng, Despina Kontos, Shonket Ray, 2015, Medical physics.

Parenchymal texture measures weighted by breast anatomy: preliminary optimization in a case-control study

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2016, SPIE Medical Imaging.

A Comparative Study of Volumetric and Area-Based Breast Density Estimation in Digital Mammography: Results from a Screening Population

Andrew D. A. Maidment, Predrag R. Bakic, Emily F. Conant, 2010, Digital Mammography / IWDM.

The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview

Christos Davatzikos, Russell T. Shinohara, Spyridon Bakas, 2019, BrainLes@MICCAI.

Predicting axillary lymph node metastasis from kinetic statistics of DCE-MRI breast images

Ahmed Bilal Ashraf, Despina Kontos, Carolyn Mies, 2012, Medical Imaging.

A Multichannel Markov Random Field Framework for Tumor Segmentation With an Application to Classification of Gene Expression-Based Breast Cancer Recurrence Risk

Mark Rosen, Ahmed Bilal Ashraf, Despina Kontos, 2013, IEEE Transactions on Medical Imaging.

Mammographic phenotypes of breast cancer risk driven by breast anatomy

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2017, Medical Imaging.

A representation and classification scheme for tree-like structures in medical images: an application on branching pattern analysis of ductal trees in x-ray galactograms

Vasileios Megalooikonomou, Andrew D. A. Maidment, Predrag R. Bakic, 2006, SPIE Medical Imaging.

Radiogenomics in brain, breast, and lung cancer: opportunities and challenges

Despina Kontos, Rhea Chitalia, Apurva Singh, 2021, Journal of medical imaging.

Intrinsic radiomics phenotypes of DCI from breast DCE-MRI: demonstrating feasibility in interim analysis of the ECOG-ACRIN E4112 trial

Despina Kontos, Constantine Gatsonis, Antonio C. Wolff, 2021, Medical Imaging.

Deep-LIBRA: Artificial intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment

Emily F. Conant, Aimilia Gastounioti, Despina Kontos, 2020, Medical Image Anal..

Radiomic features predict local failure-free survival in stage III NSCLC adenocarcinoma treated with chemoradiation

Keith A. Cengel, Bardia Yousefi, Despina Kontos, 2021, Medical Imaging.

GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging pdf

Christos Davatzikos, Spyridon Bakas, Ujjwal Baid, 2021, Communications Engineering.

Special Section Guest Editorial: Radiogenomics in Prognosis and Treatment

Karen Drukker, Despina Kontos, Hui Li, 2021, Journal of medical imaging.

Development of a radiogenomic biomarker for tumor characterization and prognosis in non-small cell lung cancer patients

Bardia Yousefi, Despina Kontos, Sharyn I. Katz, 2021, Medical Imaging.

Reader variability in breast density estimation from full-field digital mammograms: the effect of image postprocessing on relative and absolute measures.

Despina Kontos, Jinbo Chen, Emily F Conant, 2013, Academic radiology.

Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles.

Ahmed Bilal Ashraf, Michael Feldman, Despina Kontos, 2014, Radiology.

Quantitative assessment of background parenchymal enhancement in breast MRI predicts response to risk-reducing salpingo-oophorectomy: preliminary evaluation in a cohort of BRCA1/2 mutation carriers

Shandong Wu, Despina Kontos, Jinbo Chen, 2015, Breast Cancer Research.

The use of the Gail model, body mass index and SNPs to predict breast cancer among women with abnormal (BI-RADS 4) mammograms

Anne Marie McCarthy, Despina Kontos, Katrina Armstrong, 2014, Breast Cancer Research.

Variation in Mammographic Breast Density Assessments Among Radiologists in Clinical Practice: A Multicenter Observational Study.

Ronilda C. Lacson, Despina Kontos, Donald L Weaver, 2016, Annals of internal medicine.

Simultaneous assessment of gastric accommodation and emptying: studies with liquid and solid meals.

Vasileios Megalooikonomou, Despina Kontos, Robert S Fisher, 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

Detecting discriminative functional MRI activation patterns using space filling curves

Christos Faloutsos, Vasileios Megalooikonomou, Despina Kontos, 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma

Christos Davatzikos, Spyridon Bakas, Ashutosh Kumar Singh, 2020, JCO clinical cancer informatics.

Screening outcomes following implementation of digital breast tomosynthesis in a general-population screening program.

Daniel F Heitjan, Anne Marie McCarthy, Despina Kontos, 2014, Journal of the National Cancer Institute.

Breast parenchymal patterns in processed versus raw digital mammograms: A large population study toward assessing differences in quantitative measures across image representations.

Aimilia Gastounioti, Despina Kontos, Meng-Kang Hsieh, 2016, Medical physics.

Mammographic parenchymal patterns as an imaging marker of endogenous hormonal exposure: a preliminary study in a high-risk population.

Andrew D. A. Maidment, Despina Kontos, Jinbo Chen, 2013, Academic radiology.

Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment.

Andrew D. A. Maidment, Predrag R. Bakic, Emily F. Conant, 2011, Radiology.

Parenchymal texture analysis in digital breast tomosynthesis for breast cancer risk estimation: a preliminary study.

Ann-Katherine Carton, Andrew D. A. Maidment, Despina Kontos, 2009, Academic radiology.

Role of texture analysis in breast MRI as a cancer biomarker: A review

Despina Kontos, Rhea D. Chitalia, D. Kontos, 2018, Journal of magnetic resonance imaging : JMRI.

Breast percent density: estimation on digital mammograms and central tomosynthesis projections.

Ann-Katherine Carton, Andrew D. A. Maidment, Despina Kontos, 2009, Radiology.

Racial Differences in Quantitative Measures of Area and Volumetric Breast Density.

Anne Marie McCarthy, Emily F. Conant, Despina Kontos, 2016, Journal of the National Cancer Institute.

Breast DCE-MRI Kinetic Heterogeneity Tumor Markers: Preliminary Associations With Neoadjuvant Chemotherapy Response1

Bilwaj Gaonkar, Christos Davatzikos, Despina Kontos, 2015, Translational oncology.