Julius Chapiro

发表

Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space

Nicha C. Dvornek, Xiaoxiao Li, James S. Duncan, 2020, DART/DCL@MICCAI.

How I do it: a practical database management system to assist clinical research teams with data collection, organization, and reporting.

Julius Chapiro, Howard Lee, Rüdiger Schernthaner, 2015, Academic radiology.

A practical database management system to assist clinical research teams with data collecting, organization, and reporting

Julius Chapiro, Boris Gorodetski, Ruediger E. Schernthaner, 2015 .

Hepatocellular Carcinoma Intra-arterial Treatment Response Prediction for Improved Therapeutic Decision-Making pdf

Nicha C. Dvornek, James S. Duncan, Junlin Yang, 2019, ArXiv.

Liver Tissue Classification Using an Auto-context-based Deep Neural Network with a Multi-phase Training Framework

James S. Duncan, Junlin Yang, Julius Chapiro, 2018, Patch-MI@MICCAI.

Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification

Fan Zhang, Junlin Yang, Julius Chapiro, 2020, IEEE Transactions on Medical Imaging.

Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation

Fan Zhang, Nicha C. Dvornek, James S. Duncan, 2019, MICCAI.

Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation

James S. Duncan, Junlin Yang, Julius Chapiro, 2020, iMIMIC/MIL3iD/LABELS@MICCAI.

Automatic Multimodal Registration via Intraprocedural Cone-Beam CT Segmentation using MRI Distance Maps

Julius Chapiro, James Duncan, MingDe Lin, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Open trajectory cone-beam CT acquisition improves liver visualization during IR procedures

Zhijun Wang, Julius Chapiro, Ruediger E. Schernthaner, 2015 .

Supervised Machine Learning in Oncology: A Clinician's Guide

John A. Onofrey, Julius Chapiro, Nikitha Murali, 2020, Digestive Disease Interventions.

Liver Tissue Classification in Patients with Hepatocellular Carcinoma by Fusing Structured and Rotationally Invariant Context Representation

James S. Duncan, Lawrence H. Staib, John Treilhard, 2017, MICCAI.

Domain-Agnostic Learning With Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation

Juntang Zhuang, Nicha C. Dvornek, James S. Duncan, 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).

Anatomy-guided Multimodal Registration by Learning Segmentation without Ground Truth: Application to Intraprocedural CBCT/MR Liver Segmentation and Registration

James S. Duncan, Julius Chapiro, Chi Liu, 2021, Medical Image Anal..

Use of Artificial Intelligence in Nononcologic Interventional Radiology: Current State and Future Directions

Lawrence H. Staib, Julius Chapiro, Rohil Malpani, 2021, Digestive Disease Interventions.

Three-dimensional evaluation of lipiodol retention in HCC after chemoembolization: a quantitative comparison between CBCT and MDCT.

Julius Chapiro, David Lesage, Rafael Duran, 2014, Academic radiology.

The Role of Artificial Intelligence in Interventional Oncology: A Primer.

Julius Chapiro, J. Chapiro, Clinton Jia Wang, 2019, Journal of vascular and interventional radiology : JVIR.

A 3D quantitative imaging biomarker in pre-treatment MRI predicts overall survival after stereotactic radiation therapy of patients with a singular brain metastasis

Bernd Hamm, Julius Chapiro, B. Hamm, 2019, Acta radiologica.

Three-Dimensional Quantitative Assessment of Uterine Fibroid Response after Uterine Artery Embolization Using Contrast-Enhanced MR Imaging.

Julius Chapiro, Rüdiger Schernthaner, Rafael Duran, 2015, Journal of vascular and interventional radiology : JVIR.

From the Guest Editor: Interventional Oncology: The Fourth Pillar of Oncology.

Julius Chapiro, J. Geschwind, J. Chapiro, 2016, Cancer journal.