H. Akbari

发表

Blood vessel detection and artery-vein differentiation using hyperspectral imaging

Y. Kosugi, H. Akbari, K. Kojima, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Cancer detection using infrared hyperspectral imaging

Y. Kosugi, H. Akbari, K. Kojima, 2011, Cancer science.

Hyperspectral imaging and quantitative analysis for prostate cancer detection.

Luma V. Halig, H. Akbari, B. Fei, 2012, Journal of biomedical optics.

Hyperspectral imaging and diagnosis of intestinal ischemia

Y. Kosugi, H. Akbari, K. Kojima, 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Automatic 3D segmentation of the kidney in MR images using wavelet feature extraction and probability shape model

Baowei Fei, Hamed Akbari, H. Akbari, 2012, Medical Imaging.

A novel method for artery detection in laparoscopic surgery

Y. Kosugi, H. Akbari, K. Kihara, 2008, Surgical Endoscopy.

Brain Tumor Segmentation by a Generative Model with a Prior on Tumor Shape

Bjoern H Menze, Vivek S. Bharadwaj, H. Larochelle, 2015 .

Detecting Vasodilation as Potential Diagnostic Biomarker in Breast Cancer Using Deep Learning-Driven Thermomics

X. Maldague, H. Akbari, B. Yousefi, 2020, Biosensors.

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation

S. Bakas, C. Davatzikos, Bilwaj Gaonkar, 2015, Brainles@MICCAI.

Radiomic MRI signature reveals three distinct subtypes of glioblastoma with different clinical and molecular characteristics, offering prognostic value beyond IDH1

Zev A. Binder, C. Davatzikos, M. Bilello, 2018, Scientific Reports.

Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma.

G. Biros, C. Davatzikos, M. Bilello, 2016, Neurosurgery.

Histopathology‐validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo‐progression in glioblastoma

Christos Davatzikos, Spyridon Bakas, Adam P Dicker, 2020, Cancer.

3D ultrasound image segmentation using wavelet support vector machines.

Baowei Fei, Hamed Akbari, H. Akbari, 2012, Medical physics.

135 Imaging Patterns Predict Patient Survival and Molecular Subtype in Glioblastoma Using Machine Learning Techniques

Luke Macyszyn, Yingtao Bi, Sharmistha Pal, 2015 .

NIMG-41. ACCURATE AND GENERALIZABLE PRE-OPERATIVE PROGNOSTIC STRATIFICATION OF GLIOBLASTOMA PATIENTS USING INTEGRATIVE QUANTITATIVE RADIOMIC ANALYSIS OF CONVENTIONAL MRI

Christos Davatzikos, Russell T. Shinohara, Spyridon Bakas, 2017 .

NIMG-38. QUANTITATIVE IMAGING PREDICTORS OF OVERALL SURVIVAL IN GLIOBLASTOMA PATIENTS ROBUST IN THE PRESENCE OF INTER-SCANNER VARIATIONS

Christos Davatzikos, Spyridon Bakas, Saima Rathore, 2018, Neuro-Oncology.

Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma

C. Davatzikos, H. Akbari, Sumei Wang, 2022, NMR in biomedicine.

Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastoma

S. Bakas, C. Davatzikos, H. Akbari, 2022, Scientific Reports.

Arterial Spin Labeling and Dynamic Susceptibility Contrast-enhanced MR Imaging for evaluation of arteriovenous shunting and tumor hypoxia in glioblastoma

C. Davatzikos, J. Detre, H. Akbari, 2019, Scientific Reports.

Epidermal Growth Factor Receptor Extracellular Domain Mutations in Glioblastoma Present Opportunities for Clinical Imaging and Therapeutic Development.

Christos Davatzikos, Spyridon Bakas, Michel Bilello, 2018, Cancer cell.

NIMG-07. UNIFYING MAGNETIC RESONANCE IMAGING SIGNATURE OF EGFR PATHWAY ACTIVATION IN GLIOBLASTOMA CONSISTENT WITH UNIFORMLY AGGRESSIVELY INFILTRATION

Zev A. Binder, S. Bakas, C. Davatzikos, 2017 .

In Vivo Detection of EGFRvIII in Glioblastoma via Perfusion Magnetic Resonance Imaging Signature Consistent with Deep Peritumoral Infiltration: The ϕ-Index

Christos Davatzikos, Spyridon Bakas, Donald M. O'Rourke, 2017, Clinical Cancer Research.

Quanti cation of Tumor Micro-Environment Acidity in Glioblastoma Using Principal Component Analysis of Dynamic Susceptibility Contrast- Enhanced MR Imaging and Machine Learning

H. Akbari, S. Bagley, A. Kazerooni, 2021 .

In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multiparametric MRI signature

Christos Davatzikos, Spyridon Bakas, Hamed Akbari, 2018, Neuro-oncology.

Artificial intelligence-based locoregional markers of brain peritumoral microenvironment

Z. R. Samani, S. Bakas, D. Parker, 2022, Scientific Reports.

The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics

Zev A. Binder, William A. Parker, S. Bakas, 2022, Scientific Data.

NIMG-11. HIGHLY-EXPRESSED WILD-TYPE EGFR AND EGFRvIII MUTANT GLIOBLASTOMAS HAVE SIMILAR MRI SIGNATURE, CONSISTENT WITH DEEP PERITUMORAL INFILTRATION

Christos Davatzikos, Spyridon Bakas, Donald M. O'Rourke, 2016 .

NIMG-59. RADIOLOGIC SUBTYPES OF GLIOBLASTOMA CALCULATED VIA MULTI-PARAMETRIC IMAGING SIGNATURES REVEAL COMPLEMENTARY INFORMATION TO CURRENT WHO CLASSIFICATION

Christos Davatzikos, Michel Bilello, Saima Rathore, 2017 .

AI-based Prognostic Imaging Biomarkers for Precision Neurooncology: the ReSPOND Consortium.

Christos Davatzikos, Spyridon Bakas, Adam P Dicker, 2020, Neuro-oncology.

Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma

Christos Davatzikos, Ronald L. Wolf, Michel Bilello, 2016, NeuroImage: Clinical.

NIMG-44. QUANTITATIVE MULTI-PARAMETRIC IMAGE PROFILING REVEALS REMARKABLE HETEROGENEITY WITHIN IDH-WILDTYPE GLIOBLASTOMA, OFFERING PROGNOSTIC STRATIFICATION BEYOND CURRENT WHO CLASSIFICATIONS

Christos Davatzikos, Spyridon Bakas, Michel Bilello, 2018, Neuro-Oncology.

MPTH-02. EXTRACELLULAR EGFR289 ACTIVATING MUTATIONS CONFER POORER SURVIVAL AND SUGGEST ENHANCED MOTILITY IN PRIMARY GBMs

Christos Davatzikos, Spyridon Bakas, Donald M. O'Rourke, 2016 .

Radiomic Features from Multi-Institutional Glioblastoma MRI Offer Additive Prognostic Value to Clinical and Genomic Markers: Focus on TCGA-GBM Collection

Christos Davatzikos, Spyridon Bakas, Aristeidis Sotiras, 2017 .

Use of Fetal Magnetic Resonance Image Analysis and Machine Learning to Predict the Need for Postnatal Cerebrospinal Fluid Diversion in Fetal Ventriculomegaly

Christos Davatzikos, Spyridon Bakas, Saima Rathore, 2017, JAMA pediatrics.

NIMG-70. QUANTITATIVE IMAGE ANALYSIS AND MACHINE LEARNING TECHNIQUES FOR DISTINGUISHING TRUE PROGRESSION FROM PSEUDOPROGRESSION IN PATIENTS WITH GLIOBLASTOMA

Christos Davatzikos, Spyridon Bakas, Ronald L. Wolf, 2018, Neuro-Oncology.

NIMG-20. IMAGING PATTERN ANALYSIS REVEALS THREE DISTINCT PHENOTYPIC SUBTYPES OF GBM WITH DIFFERENT SURVIVAL RATES

Christos Davatzikos, Spyridon Bakas, Saima Rathore, 2016 .

NIMG-45. MULTIVARIATE PATTERN ANALYSIS OF DE NOVO GLIOBLASTOMA PATIENTS OFFERS IN VIVO EVALUATION OF O6-METHYLGUANINE-DNA-METHYLTRANSFERASE (MGMT) PROMOTER METHYLATION STATUS, COMPENSATING FOR INSUFFICIENT SPECIMEN AND ASSAY FAILURES

Christos Davatzikos, Spyridon Bakas, Saima Rathore, 2018, Neuro-Oncology.

Hyperspectral Imaging: a New Modality in Surgery

Yukio Kosugi, Hamed Akbari, Y. Kosugi, 2009 .

Predicting pediatric optic pathway glioma progression using advanced magnetic resonance image analysis and machine learning

C. Davatzikos, H. Akbari, A. Vossough, 2020, Neuro-oncology advances.

The Radiogenomic and Spatiogenomic Landscapes of Glioblastoma, and their Relationship to Oncogenic Drivers

Ashutosh Kumar Singh, Zev A. Binder, S. Bakas, 2022, bioRxiv.

SPAER: Sparse Deep Convolutional Autoencoder Model to Extract Low Dimensional Imaging Biomarkers for Early Detection of Breast Cancer Using Dynamic Thermography

S. Ahadian, X. Maldague, H. Akbari, 2021, Applied Sciences.

PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration

Christos Davatzikos, Kilian M. Pohl, Marc Niethammer, 2014, IEEE Transactions on Medical Imaging.

Impartially Validated Multiple Deep-Chain Models to Detect COVID-19 in Chest X-ray Using Latent Space Radiomics

S. Ahadian, X. Maldague, H. Akbari, 2021, Journal of clinical medicine.

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques.

Luke Macyszyn, Christos Davatzikos, Yingtao Bi, 2016, Neuro-oncology.

Overall survival prediction in glioblastoma patients using structural magnetic resonance imaging (MRI): advanced radiomic features may compensate for lack of advanced MRI modalities

Christos Davatzikos, Michel Bilello, Gaurav Shukla, 2020, Journal of 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.

Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma

Christos Davatzikos, Ragini Verma, Spyridon Bakas, 2017, BrainLes@MICCAI.

Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

Christos Davatzikos, Spyridon Bakas, Michel Bilello, 2017, Scientific Data.

Segmentation of Gliomas in Pre-operative and Post-operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework

Christos Davatzikos, Spyridon Bakas, Aristeidis Sotiras, 2016, BrainLes@MICCAI.

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation

Bilwaj Gaonkar, Christos Davatzikos, Spyridon Bakas, 2015, Brainles@MICCAI.

Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of de novo Glioblastoma Patients

Christos Davatzikos, Ramana V. Davuluri, Spyridon Bakas, 2019, Front. Comput. Neurosci..

Non-invasive transcriptomic classification of de novo Glioblastoma patients through multivariate quantitative analysis of baseline preoperative multimodal magnetic resonance imaging

Christos Davatzikos, Spyridon Bakas, Donald M. O'Rourke, 2019, Medical Imaging.

Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine

S. Bakas, C. Davatzikos, H. Akbari, 2021, Cancers.

Radiomic MRI signature reveals three distinct subtypes of glioblastoma with different clinical and molecular characteristics, offering prognostic value beyond IDH1

Zev A. Binder, C. Davatzikos, M. Bilello, 2018, Scientific Reports.

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.

Multi-institutional noninvasive in vivo characterization of IDH, 1p/19q, and EGFRvIII in glioma using neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk)

Ashutosh Kumar Singh, D. Kontos, S. Bakas, 2020, Neuro-oncology advances.

Technical note: a radiomic signature of infiltration in peritumoral edema predicts subsequent recurrence in glioblastoma

Christos Davatzikos, Jimit Doshi, Michel Bilello, 2018, Medical Imaging.

Radiomic signature of infiltration in peritumoral edema predicts subsequent recurrence in glioblastoma: implications for personalized radiotherapy planning

Christos Davatzikos, Jimit Doshi, Michel Bilello, 2018, Journal of medical imaging.

Combining Generative Models for Multifocal Glioma Segmentation and Registration

Christos Davatzikos, Russell T. Shinohara, Dongjin Kwon, 2014, MICCAI.

Integrative radiomic analysis for pre-surgical prognostic stratification of glioblastoma patients: from advanced to basic MRI protocols

Christos Davatzikos, Michel Bilello, Russell T. Shinohara, 2020, Medical Imaging: Image-Guided Procedures.

Patient-Specific Registration of Pre-operative and Post-recurrence Brain Tumor MRI Scans

Xu Han, Christos Davatzikos, Spyridon Bakas, 2018, BrainLes@MICCAI.

Image-guided preparation of the calot's triangle in laparoscopic cholecystectomy

Y. Kosugi, H. Akbari, Z. Khorgami, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

The Brain Tumor Sequence Registration Challenge: Establishing Correspondence between Pre-Operative and Follow-up MRI scans of diffuse glioma patients pdf

Christos Davatzikos, Spyridon Bakas, Bhakti Baheti, 2021, ArXiv.

Enhanced Blood Vessels in Laparoscopy by Using Narrow-Band Imaging

Yukio Kosugi, Kazuyuki Kojima, Naofumi Tanaka, 2007, MVA.

Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging

C. Davatzikos, H. Akbari, S. Brem, 2021, Scientific Reports.

Robust Image Population Based Stain Color Normalization: How Many Reference Slides Are Enough?

Caleb M. Grenko, Angela N. Viaene, S. Bakas, 2022, IEEE Open Journal of Engineering in Medicine and Biology.

Detection and Analysis of the Intestinal Ischemia Using Visible and Invisible Hyperspectral Imaging

Yukio Kosugi, Kazuyuki Kojima, Naofumi Tanaka, 2010, IEEE Transactions on Biomedical Engineering.

Automated tumor volumetry using computer-aided image segmentation.

Bilwaj Gaonkar, Luke Macyszyn, Christos Davatzikos, 2015, Academic radiology.

Pattern analysis of dynamic susceptibility contrast-enhanced MR imaging demonstrates peritumoral tissue heterogeneity.

Luke Macyszyn, Christos Davatzikos, Ragini Verma, 2014, Radiology.

The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview

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

3D segmentation of prostate ultrasound images using wavelet transform

Baowei Fei, Hamed Akbari, Xiaofeng Yang, 2011, Medical Imaging.

Reproducibility analysis of multi-institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset.

Ruchika Verma, Pallavi Tiwari, Michel Bilello, 2020, Medical physics.

NIMG-40. NON-INVASIVE IN VIVO SIGNATURE OF IDH1 MUTATIONAL STATUS IN HIGH GRADE GLIOMA, FROM CLINICALLY-ACQUIRED MULTI-PARAMETRIC MAGNETIC RESONANCE IMAGING, USING MULTIVARIATE MACHINE LEARNING

Christos Davatzikos, Spyridon Bakas, Saima Rathore, 2018, Neuro-Oncology.

Comparative Evaluation of Registration Algorithms in Different Brain Databases With Varying Difficulty: Results and Insights

Christos Davatzikos, Michel Bilello, Yangming Ou, 2014, IEEE Transactions on Medical Imaging.

Deriving stable multi-parametric MRI radiomic signatures in the presence of inter-scanner variations: survival prediction of glioblastoma via imaging pattern analysis and machine learning techniques

Christos Davatzikos, Spyridon Bakas, Gaurav Shukla, 2018, Medical Imaging.

Interactive Machine Learning-Based Multi-Label Segmentation of Solid Tumors and Organs

Amber L. Simpson, Sharyn I. Katz, D. Kontos, 2021, Applied sciences.

Estimating Glioblastoma Biophysical Growth Parameters Using Deep Learning Regression

Siddhesh P. Thakur, G. Biros, S. Bakas, 2020, BrainLes@MICCAI.

A molecular image-directed, 3D ultrasound-guided biopsy system for the prostate

Aaron Fenster, Baowei Fei, Hamed Akbari, 2012, Medical Imaging.

A PET/CT Directed, 3D Ultrasound-Guided Biopsy System for Prostate Cancer

Aaron Fenster, Baowei Fei, Hamed Akbari, 2011, Prostate Cancer Imaging.

Arterial Spin Labeling and Dynamic Susceptibility Contrast-enhanced MR Imaging for evaluation of arteriovenous shunting and tumor hypoxia in glioblastoma

C. Davatzikos, J. Detre, H. Akbari, 2019, Scientific Reports.

Leveraging machine learning predictive biomarkers to augment the statistical power of clinical trials with baseline magnetic resonance imaging

R. Lipton, C. Davatzikos, H. Akbari, 2021, Brain communications.

Wavelet-Based Compression and Segmentation of Hyperspectral Images in Surgery

Yukio Kosugi, Kazuyuki Kojima, Naofumi Tanaka, 2008, MIAR.

A New Technique for Laparoscopic Image Segmentation and Blood Vessels Detection

Y. Kosugi, H. Akbari, K. Kojima, 2006 .

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium

Zev A. Binder, Peter I. Kamel, Susan M. Chang, 2023, Neuroradiology.

3D non-rigid registration using surface and local salient features for transrectal ultrasound image-guided prostate biopsy

Baowei Fei, Hamed Akbari, Xiaofeng Yang, 2011, Medical Imaging.

Hyperspectral Image segmentation and its application in abdominal surgery

Yukio Kosugi, Kazuyuki Kojima, Naofumi Tanaka, 2009, Int. J. Funct. Informatics Pers. Medicine.

Detection of cancer metastasis using a novel macroscopic hyperspectral method

Zhuo Georgia Chen, Baowei Fei, Hongzheng Zhang, 2012, Medical Imaging.

A Deep Network for Joint Registration and Reconstruction of Images with Pathologies pdf

Christos Davatzikos, Spyridon Bakas, Marc Niethammer, 2020, MLMI@MICCAI.

Correlations of atrial diameter and frontooccipital horn ratio with ventricle size in fetal ventriculomegaly.

S. Bakas, C. Davatzikos, H. Akbari, 2017, Journal of neurosurgery. Pediatrics.

Hyperspectral imaging and spectral-spatial classification for cancer detection

Baowei Fei, Hamed Akbari, Luma V. Halig, 2012, 2012 5th International Conference on BioMedical Engineering and Informatics.

Incendia and Fractal Architecture

H. Akbari, Mehdi Amiri, M. Garousi, 2011 .

Hyperspectral imaging and quantitative analysis for prostate cancer detection.

Luma V. Halig, H. Akbari, B. Fei, 2012, Journal of biomedical optics.

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques.

G. Biros, C. Davatzikos, M. Bilello, 2016, Neuro-oncology.

The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview.

Siddhesh P. Thakur, D. Kontos, S. Bakas, 2019, Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries. BrainLes.

Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approach

Zev A. Binder, S. Bakas, H. Akbari, 2024, Scientific reports.

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.

Alessandro Crimi, S. Bakas, Bilwaj Gaonkar, 2015, Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries. BrainLes.