Publications by authors named "Noel Codella"

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From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification.
Xue Li, Jameson Merkow, Noel C F Codella, Alberto Santamaria-Pang, Naiteek Sangani

J Imaging Inform Med· December 2025

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Automated triage of cancer-suspicious skin lesions with 3D total-body photography.
Nicholas R Kurtansky, Maura C Gillis, Noel C F Codella, Brian M D'Alessandro, Zongyuan Ge

NPJ Digit Med· November 2025

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BCN20000: Dermoscopic Lesions in the Wild.
Carlos Hernández-Pérez, Marc Combalia, Sebastian Podlipnik, Noel C F Codella, Veronica Rotemberg

Sci Data· June 2024

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Expert Agreement on the Presence and Spatial Localization of Melanocytic Features in Dermoscopy.
Konstantinos Liopyris, Cristian Navarrete-Dechent, Michael A Marchetti, Veronica Rotemberg, Zoe Apalla, Noel C F Codella

J Invest Dermatol· March 2024

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A reinforcement learning model for AI-based decision support in skin cancer.
Catarina Barata, Veronica Rotemberg, Noel C F Codella, Philipp Tschandl, Christoph Rinner

Nat Med· August 2023

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Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge.
Marc Combalia, Noel Codella, Veronica Rotemberg, Cristina Carrera, Stephen Dusza

Lancet Digit Health· May 2022

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Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology: CLEAR Derm Consensus Guidelines From the International Skin Imaging Collaboration Artificial Intelligence Working Group.
Roxana Daneshjou, Catarina Barata, Brigid Betz-Stablein, M Emre Celebi, Noel Codella

JAMA Dermatol· January 2022

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Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context.
Veronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, Liam Caffery, Emmanouil Chousakos, Noel Codella

Sci Data· March 2021

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Publisher Correction: Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context.
Veronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, Liam Caffery, Emmanouil Chousakos, Noel Codella

Sci Data· March 2021

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A patient-centric dataset of images and metadata for identifying melanomas using clinical context.
Veronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, Liam Caffery, Emmanouil Chousakos, Noel Codella

Sci Data· January 2021

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Human-computer collaboration for skin cancer recognition.
Philipp Tschandl, Christoph Rinner, Zoe Apalla, Giuseppe Argenziano, Noel Codella

Nat Med· August 2020

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Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.
Michael A Marchetti, Konstantinos Liopyris, Stephen W Dusza, Noel C F Codella, David A Gutman

J Am Acad Dermatol· March 2020

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Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.
Philipp Tschandl, Noel Codella, Bengü Nisa Akay, Giuseppe Argenziano, Ralph P Braun

Lancet Oncol· July 2019

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Dermoscopy Image Analysis: Overview and Future Directions.
M Emre Celebi, Noel Codella, Allan Halpern

IEEE J Biomed Health Inform· March 2019

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The role of public challenges and data sets towards algorithm development, trust, and use in clinical practice.
Veronica Rotemberg, Allan Halpern, Steven Dusza, Noel Cf Codella

Semin Cutan Med Surg· March 2019

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Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.
Alex Bratt, Jiwon Kim, Meridith Pollie, Ashley N Beecy, Nathan H Tehrani, Noel Codella

J Cardiovasc Magn Reson· January 2019

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Segmentation of Both Diseased and Healthy Skin From Clinical Photographs in a Primary Care Setting.
Noel C F Codella, Daren Anderson, Tyler Philips, Anthony Porto, Kevin Massey

Annu Int Conf IEEE Eng Med Biol Soc· July 2018

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Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images.
Michael A Marchetti, Noel C F Codella, Stephen W Dusza, David A Gutman, Brian Helba

J Am Acad Dermatol· February 2018

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Multi-scale classification based lesion segmentation for dermoscopic images.
Mani Abedini, Noel Codella, Rajib Chakravorty, Rahil Garnavi, David Gutman

Annu Int Conf IEEE Eng Med Biol Soc· August 2016

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Echocardiographic Algorithm for Post-Myocardial Infarction LV Thrombus: A Gatekeeper for Thrombus Evaluation by Delayed Enhancement CMR.
Jonathan W Weinsaft, Jiwon Kim, Chaitanya B Medicherla, Claudia L Ma, Noel C F Codella

JACC Cardiovasc Imaging· May 2016

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Left ventricle: fully automated segmentation based on spatiotemporal continuity and myocardium information in cine cardiac magnetic resonance imaging (LV-FAST).
Lijia Wang, Mengchao Pei, Noel C F Codella, Minisha Kochar, Jonathan W Weinsaft

Biomed Res Int· November 2015

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Automated medical image modality recognition by fusion of visual and text information.
Noel Codella, Jonathan Connell, Sharath Pankanti, Michele Merler, John R Smith

Med Image Comput Comput Assist Interv· January 2015

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Geometry-independent inclusion of basal myocardium yields improved cardiac magnetic resonance agreement with echocardiography and necropsy quantified left-ventricular mass.
Lauren A Simprini, Parag Goyal, Noel Codella, David S Fieno, Anika Afroz

J Hypertens· October 2013

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Improved left ventricular mass quantification with partial voxel interpolation: in vivo and necropsy validation of a novel cardiac MRI segmentation algorithm.
Noel C F Codella, Hae Yeoun Lee, David S Fieno, Debbie W Chen, Sandra Hurtado-Rua

Circ Cardiovasc Imaging· January 2012

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A radial self-calibrated (RASCAL) generalized autocalibrating partially parallel acquisition (GRAPPA) method using weight interpolation.
Noel C F Codella, Pascal Spincemaille, Martin Prince, Yi Wang

NMR Biomed· August 2011

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