Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Jenika Karcich

Showing results (1-10 of 13) with videos related to

Pageof 2
Sort By:
Journal of Vascular and Interventional Radiology : JVIR|May 25, 2015
Percutaneous embolization of a post-thoracic endovascular aortic repair aortic sac-bronchial fistula with N-butyl cyanoacrylateDhruv Patel, Jenika Karcich, Sohail Contractor
Skeletal Radiology|February 22, 2019
Bennett lesions in overhead athletes and associated shoulder abnormalities on MRIJenika Karcich, Jonathan K Kazam, Michael J Rasiej, et al.
Eplasty|October 21, 2014
The Use of Fetal Bovine Dermal Scaffold (PriMatrix) in the Management of Full-Thickness Hand BurnsAlexis Lanteri Parcells, Jenika Karcich, Mark S Granick, et al.
Academic Radiology|August 4, 2018
Convolutional Neural Network Based Breast Cancer Risk Stratification Using a Mammographic DatasetRichard Ha, Peter Chang, Jenika Karcich, et al.
Journal of Digital Imaging|April 27, 2018
Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI DatasetRichard Ha, Peter Chang, Jenika Karcich, et al.
AJR. American Journal of Roentgenology|March 13, 2019
Accuracy of Distinguishing Atypical Ductal Hyperplasia From Ductal Carcinoma In Situ With Convolutional Neural Network-Based Machine Learning Approach Using Mammographic Image DataRichard Ha, Simukayi Mutasa, Eduardo Pascual Van Sant, et al.
Journal of Magnetic Resonance Imaging : JMRI|August 22, 2018
Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence ScoreRichard Ha, Peter Chang, Simukayi Mutasa, et al.
Journal of Digital Imaging|August 5, 2018
Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal EnhancementRichard Ha, Peter Chang, Eralda Mema, et al.
Academic Radiology|September 19, 2019
Potential Role of Convolutional Neural Network Based Algorithm in Patient Selection for DCIS Observation Trials Using a Mammogram DatasetSimukayi Mutasa, Peter Chang, Eduardo P Van Sant, et al.
Journal of Magnetic Resonance Imaging : JMRI|June 25, 2017
Does breast MRI background parenchymal enhancement indicate metabolic activity? Qualitative and 3D quantitative computer imaging analysisEralda Mema, Victoria L Mango, Xiaotao Guo, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
Journal of Vascular and Interventional Radiology : JVIR|May 25, 2015
Percutaneous embolization of a post-thoracic endovascular aortic repair aortic sac-bronchial fistula with N-butyl cyanoacrylateDhruv Patel, Jenika Karcich, Sohail Contractor
Skeletal Radiology|February 22, 2019
Bennett lesions in overhead athletes and associated shoulder abnormalities on MRIJenika Karcich, Jonathan K Kazam, Michael J Rasiej, et al.
Eplasty|October 21, 2014
The Use of Fetal Bovine Dermal Scaffold (PriMatrix) in the Management of Full-Thickness Hand BurnsAlexis Lanteri Parcells, Jenika Karcich, Mark S Granick, et al.
Academic Radiology|August 4, 2018
Convolutional Neural Network Based Breast Cancer Risk Stratification Using a Mammographic DatasetRichard Ha, Peter Chang, Jenika Karcich, et al.
Journal of Digital Imaging|April 27, 2018
Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI DatasetRichard Ha, Peter Chang, Jenika Karcich, et al.
AJR. American Journal of Roentgenology|March 13, 2019
Accuracy of Distinguishing Atypical Ductal Hyperplasia From Ductal Carcinoma In Situ With Convolutional Neural Network-Based Machine Learning Approach Using Mammographic Image DataRichard Ha, Simukayi Mutasa, Eduardo Pascual Van Sant, et al.
Journal of Magnetic Resonance Imaging : JMRI|August 22, 2018
Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence ScoreRichard Ha, Peter Chang, Simukayi Mutasa, et al.
Journal of Digital Imaging|August 5, 2018
Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal EnhancementRichard Ha, Peter Chang, Eralda Mema, et al.
Academic Radiology|September 19, 2019
Potential Role of Convolutional Neural Network Based Algorithm in Patient Selection for DCIS Observation Trials Using a Mammogram DatasetSimukayi Mutasa, Peter Chang, Eduardo P Van Sant, et al.
Journal of Magnetic Resonance Imaging : JMRI|June 25, 2017
Does breast MRI background parenchymal enhancement indicate metabolic activity? Qualitative and 3D quantitative computer imaging analysisEralda Mema, Victoria L Mango, Xiaotao Guo, et al.
Pageof 2