Digital pathology image analysis: opportunities and challenges

di Madabhushi, Anant
Pubblicato in Imaging Med (2009)

Graphical processing unit implementation of an integrated shape-based active contour: Application to digital pathology

di Ali, Sahirzeeshan, Madabhushi, Anant
Pubblicazione 2012

Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data

di Viswanath, Satish, Madabhushi, Anant
Pubblicazione 2012

Statistical Shape Model for Manifold Regularization: Gleason grading of prostate histology

di Sparks, Rachel, Madabhushi, Anant
Pubblicazione 2013

Explicit shape descriptors: Novel morphologic features for histopathology classification

di Sparks, Rachel, Madabhushi, Anant
Pubblicazione 2013

Out-of-Sample Extrapolation utilizing Semi-Supervised Manifold Learning (OSE-SSL): Content Based Image Retrieval for Histopathology Images

di Sparks, Rachel, Madabhushi, Anant
Pubblicato in Sci Rep (2016)

Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

di Janowczyk, Andrew, Madabhushi, Anant
Pubblicato in J Pathol Inform (2016)

Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology

di Bhargava, Rohit, Madabhushi, Anant
Pubblicato in Annu Rev Biomed Eng (2016)

Image analysis and machine learning in digital pathology: Challenges and opportunities

di Madabhushi, Anant, Lee, George
Pubblicato in Med Image Anal (2016)

Class-Specific Weighting for Markov Random Field Estimation: Application to Medical Image Segmentation

di Monaco, James P., Madabhushi, Anant
Pubblicazione 2012

A Hierarchical Unsupervised Spectral Clustering Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy (MRS)

di Tiwari, Pallavi, Madabhushi, Anant, Rosen, Mark
Pubblicazione 2007

Investigating the Efficacy of Nonlinear Dimensionality Reduction Schemes in Classifying Gene- and Protein-Expression Studies

di Lee, George, Rodriguez, Carlos, Madabhushi, Anant
Pubblicazione 2008

A hierarchical spectral clustering and nonlinear dimensionality reduction scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS)

di Tiwari, Pallavi, Rosen, Mark, Madabhushi, Anant
Pubblicazione 2009

Quantifying local heterogeneity via morphologic scale: Distinguishing tumoral from stromal regions

di Janowczyk, Andrew, Chandran, Sharat, Madabhushi, Anant
Pubblicazione 2013

Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS

di Tiwari, Pallavi, Kurhanewicz, John, Madabhushi, Anant
Pubblicazione 2012

Identifying MRI markers to evaluate early treatment related changes post laser ablation for cancer pain management

di Tiwari, Pallavi, Danish, Shabbar, Madabhushi, Anant
Pubblicazione 2014

Identifying MRI Markers Associated with Early Response following Laser Ablation for Neurological Disorders: Preliminary Findings

di Tiwari, Pallavi, Danish, Shabbar, Madabhushi, Anant
Pubblicato in PLoS One (2014)

Predicting Classifier Performance with Limited Training Data: Applications to Computer-Aided Diagnosis in Breast and Prostate Cancer

di Basavanhally, Ajay, Viswanath, Satish, Madabhushi, Anant
Pubblicato in PLoS One (2015)

Content-based image retrieval of digitized histopathology in boosted spectrally embedded spaces

di Sridhar, Akshay, Doyle, Scott, Madabhushi, Anant
Pubblicato in J Pathol Inform (2015)

Quantifying Post- Laser Ablation Prostate Therapy Changes on MRI via a Domain-Specific Biomechanical Model: Preliminary Findings

di Toth, Robert, Sperling, Dan, Madabhushi, Anant
Pubblicato in PLoS One (2016)