Noel Codella

7.4k total citations · 1 hit paper
46 papers, 2.3k citations indexed

About

Noel Codella is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Noel Codella has authored 46 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 16 papers in Artificial Intelligence and 15 papers in Computer Vision and Pattern Recognition. Recurrent topics in Noel Codella's work include Cardiac Imaging and Diagnostics (17 papers), AI in cancer detection (11 papers) and Cardiovascular Function and Risk Factors (11 papers). Noel Codella is often cited by papers focused on Cardiac Imaging and Diagnostics (17 papers), AI in cancer detection (11 papers) and Cardiovascular Function and Risk Factors (11 papers). Noel Codella collaborates with scholars based in United States, Spain and Austria. Noel Codella's co-authors include Allan C. Halpern, M. Emre Celebi, Jonathan W. Weinsaft, Martin R. Prince, Harald Kittler, Josep Malvehy, H. Peter Soyer, Philipp Tschandl, Matthew D. Cham and Brian Helba and has published in prestigious journals such as Nature Medicine, Radiology and Magnetic Resonance in Medicine.

In The Last Decade

Noel Codella

42 papers receiving 2.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Human–computer collaboration for skin cancer recognition

2020 514 citations Philipp Tschandl, Claus Rinner et al. Nature Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Noel Codella United States	23	883	846	705	487	338	46	2.3k
S. M. Reza Soroushmehr United States	20	505 0.6×	392 0.5×	463 0.7×	63 0.1×	176 0.5×	95	1.8k
Chunliang Wang Sweden	21	526 0.6×	480 0.6×	480 0.7×	71 0.1×	210 0.6×	67	1.5k
Ashish Sharma United States	25	1.1k 1.2×	165 0.2×	711 1.0×	637 1.3×	302 0.9×	81	2.6k
Titus J. Brinker Germany	28	1.4k 1.6×	1.4k 1.6×	857 1.2×	24 0.0×	420 1.2×	105	3.0k
D.M. Jukic United States	26	784 0.9×	967 1.1×	328 0.5×	34 0.1×	324 1.0×	107	2.7k
Muhammad Khalid Khan Niazi United States	19	745 0.8×	354 0.4×	604 0.9×	27 0.1×	191 0.6×	86	1.6k
Saeed Hassanpour United States	24	926 1.0×	576 0.7×	751 1.1×	21 0.0×	245 0.7×	80	2.1k
Lucian Beer Austria	23	293 0.3×	193 0.2×	767 1.1×	85 0.2×	192 0.6×	82	1.9k
Darren Treanor United Kingdom	30	1.7k 2.0×	1.2k 1.5×	1.0k 1.4×	29 0.1×	274 0.8×	145	3.8k
Ali Madani United States	14	619 0.7×	99 0.1×	773 1.1×	308 0.6×	95 0.3×	17	2.5k

Countries citing papers authored by Noel Codella

Since Specialization

Citations

This map shows the geographic impact of Noel Codella's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Noel Codella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Noel Codella more than expected).

Fields of papers citing papers by Noel Codella

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Noel Codella. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Noel Codella. The network helps show where Noel Codella may publish in the future.

Co-authorship network of co-authors of Noel Codella

This figure shows the co-authorship network connecting the top 25 collaborators of Noel Codella. A scholar is included among the top collaborators of Noel Codella based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Noel Codella. Noel Codella is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Combalia, Marc, Sebastián Podlipnik, Noel Codella, et al.. (2024). BCN20000: Dermoscopic Lesions in the Wild. Scientific Data. 11(1). 641–641. 36 indexed citations

Yang, Ziyi, Mahmoud Khademi, Xu Yi‐chong, et al.. (2024). i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data. 1615–1627. 2 indexed citations

Barata, Catarina, Veronica Rotemberg, Noel Codella, et al.. (2023). A reinforcement learning model for AI-based decision support in skin cancer. Nature Medicine. 29(8). 1941–1946. 50 indexed citations

You, Haoxuan, et al.. (2023). UniFine: A Unified and Fine-grained Approach for Zero-shot Vision-Language Understanding. 778–793.

Yang, Ziyi, Yuwei Fang, Chenguang Zhu, et al.. (2023). i-Code: An Integrative and Composable Multimodal Learning Framework. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 10880–10890. 20 indexed citations

Chen, Long, Haoxuan You, Yicheng He, et al.. (2023). Dataset Bias Mitigation in Multiple-Choice Visual Question Answering and Beyond. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 8598–8617.

Combalia, Marc, Noel Codella, Veronica Rotemberg, et al.. (2022). Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge. The Lancet Digital Health. 4(5). e330–e339. 74 indexed citations

Tschandl, Philipp, Claus Rinner, Zoé Apalla, et al.. (2020). Human–computer collaboration for skin cancer recognition. Nature Medicine. 26(8). 1229–1234. 514 indexed citations breakdown →

Guo, Yunhui, Noel Codella, Leonid Karlinsky, et al.. (2019). A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning.. arXiv (Cornell University). 20 indexed citations

10.

Kim, Jiwon, Ashley Beecy, Noel Codella, et al.. (2019). Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification. Journal of Cardiovascular Magnetic Resonance. 21(1). 1–1. 62 indexed citations

11.

Rotemberg, Veronica, et al.. (2019). The role of public challenges and data sets towards algorithm development, trust, and use in clinical practice. Seminars in Cutaneous Medicine and Surgery. 38(1). E38–E42. 15 indexed citations

12.

Weinsaft, Jonathan W., Jiwon Kim, Chaitanya Medicherla, et al.. (2015). Echocardiographic Algorithm for Post–Myocardial Infarction LV Thrombus. JACC. Cardiovascular imaging. 9(5). 505–515. 125 indexed citations

13.

Goyal, Parag, Noel Codella, David S. Fieno, et al.. (2013). Geometry-independent inclusion of basal myocardium yields improved cardiac magnetic resonance agreement with echocardiography and necropsy quantified left-ventricular mass. Journal of Hypertension. 31(10). 2069–2076. 6 indexed citations

14.

Cao, Liangliang, et al.. (2012). IBM T.J. Watson Research Center, Multimedia Analytics: Modality Classification and Case-Based Retrieval Tasks of ImageCLEF2012.. 2 indexed citations

15.

Codella, Noel, Matthew D. Cham, Richard Wong, et al.. (2010). Rapid and accurate left ventricular chamber quantification using a novel CMR segmentation algorithm: A clinical validation study. Journal of Magnetic Resonance Imaging. 31(4). 845–853. 26 indexed citations

16.

Mendoza, Dorinna D., Noel Codella, Yi Wang, et al.. (2010). Impact of diastolic dysfunction severity on global left ventricular volumetric filling - assessment by automated segmentation of routine cine cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance. 12(1). 46–46. 46 indexed citations

17.

Lee, Hae-Yeoun, et al.. (2009). Automatic Left Ventricle Segmentation Using Iterative Thresholding and an Active Contour Model With Adaptation on Short-Axis Cardiac MRI. IEEE Transactions on Biomedical Engineering. 57(4). 905–913. 94 indexed citations

18.

Codella, Noel, Jonathan W. Weinsaft, Matthew D. Cham, et al.. (2008). Left Ventricle: Automated Segmentation by Using Myocardial Effusion Threshold Reduction and Intravoxel Computation at MR Imaging. Radiology. 248(3). 1004–1012. 52 indexed citations

19.

Codella, Noel, et al.. (2008). Left ventricle segmentation using graph searching on intensity and gradient and a priori knowledge (lvGIGA) for short‐axis cardiac magnetic resonance imaging. Journal of Magnetic Resonance Imaging. 28(6). 1393–1401. 24 indexed citations

20.

Janik, Matthew, Matthew D. Cham, Yi Wang, et al.. (2008). Effects of papillary muscles and trabeculae on left ventricular quantification: increased impact of methodological variability in patients with left ventricular hypertrophy. Journal of Hypertension. 26(8). 1677–1685. 61 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact