Kiho Im

4.5k total citations
75 papers, 2.8k citations indexed

About

Kiho Im is a scholar working on Pediatrics, Perinatology and Child Health, Radiology, Nuclear Medicine and Imaging and Cognitive Neuroscience. According to data from OpenAlex, Kiho Im has authored 75 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Pediatrics, Perinatology and Child Health, 34 papers in Radiology, Nuclear Medicine and Imaging and 20 papers in Cognitive Neuroscience. Recurrent topics in Kiho Im's work include Advanced Neuroimaging Techniques and Applications (33 papers), Fetal and Pediatric Neurological Disorders (27 papers) and Neonatal and fetal brain pathology (24 papers). Kiho Im is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (33 papers), Fetal and Pediatric Neurological Disorders (27 papers) and Neonatal and fetal brain pathology (24 papers). Kiho Im collaborates with scholars based in United States, South Korea and Canada. Kiho Im's co-authors include P. Ellen Grant, Sun I. Kim, Sang Won Seo, Jong Min Lee, Alan C. Evans, Uicheul Yoon, Sung Tae Kim, Duk L. Na, Duk L. Na and Seung Hyun Kim and has published in prestigious journals such as Science, PLoS ONE and NeuroImage.

In The Last Decade

Kiho Im

72 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kiho Im United States 28 1.2k 1.0k 780 488 371 75 2.8k
Güray Erus United States 33 1.7k 1.4× 1.2k 1.2× 1.0k 1.3× 308 0.6× 553 1.5× 116 4.0k
Douglas Dean United States 32 1.2k 1.0× 1.3k 1.3× 486 0.6× 1.0k 2.1× 401 1.1× 104 3.5k
Natalie A. Royle United Kingdom 29 1.0k 0.9× 979 1.0× 791 1.0× 276 0.6× 410 1.1× 64 3.1k
Andrea Parolin Jackowski Brazil 38 1.3k 1.1× 682 0.7× 794 1.0× 395 0.8× 190 0.5× 149 4.1k
Inge K. Amlien Norway 24 1.8k 1.5× 1.1k 1.1× 810 1.0× 328 0.7× 432 1.2× 42 3.0k
Paulina Due‐Tønnessen Norway 38 2.0k 1.7× 2.1k 2.1× 808 1.0× 820 1.7× 364 1.0× 80 5.1k
Édouard Duchesnay France 26 1.2k 1.0× 930 0.9× 505 0.6× 356 0.7× 172 0.5× 77 2.5k
Katja Franke Germany 19 1.6k 1.4× 830 0.8× 972 1.2× 525 1.1× 378 1.0× 27 3.0k
Natasha Leporé United States 26 832 0.7× 986 1.0× 465 0.6× 361 0.7× 318 0.9× 135 2.5k
Jenni Pacheco United States 9 1.6k 1.4× 1.2k 1.2× 876 1.1× 224 0.5× 344 0.9× 9 3.0k

Countries citing papers authored by Kiho Im

Since Specialization
Citations

This map shows the geographic impact of Kiho Im'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 Kiho Im with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kiho Im more than expected).

Fields of papers citing papers by Kiho Im

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kiho Im. 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 Kiho Im. The network helps show where Kiho Im may publish in the future.

Co-authorship network of co-authors of Kiho Im

This figure shows the co-authorship network connecting the top 25 collaborators of Kiho Im. A scholar is included among the top collaborators of Kiho Im 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 Kiho Im. Kiho Im is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Yun, Hyuk Jin, Anjali Sadhwani, Henry A. Feldman, et al.. (2025). Foetal cortical expansion is associated with neurodevelopmental outcome at 2-years in congenital heart disease: a longitudinal follow-up study. EBioMedicine. 114. 105679–105679. 1 indexed citations
3.
Yun, Hyuk Jin, Joo Young Lee, Lana Vasung, et al.. (2025). Deep Learning–based Brain Age Prediction Using MRI to Identify Fetuses with Cerebral Ventriculomegaly. Radiology Artificial Intelligence. 7(2). e240115–e240115. 3 indexed citations
4.
Madan, Neel, Taysir Mahmoud, Hyuk Jin Yun, et al.. (2025). Impact of high maternal body mass index on fetal cerebral cortical and cerebellar volumes. Journal of Perinatal Medicine. 53(3). 376–386. 1 indexed citations
5.
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Yun, Hyuk Jin, Usha D. Nagaraj, P. Ellen Grant, et al.. (2024). A Prospective Multi-Institutional Study Comparing the Brain Development in the Third Trimester between Opioid-Exposed and Nonexposed Fetuses Using Advanced Fetal MR Imaging Techniques. American Journal of Neuroradiology. 45(2). 218–223. 1 indexed citations
7.
Lee, Joo Young, Hyun Ju Lee, Hyuna Kim, et al.. (2023). Maternal pre-pregnancy obesity affects the uncinate fasciculus white matter tract in preterm infants. Frontiers in Pediatrics. 11. 1225960–1225960. 5 indexed citations
8.
Ahtam, Banu, Hyuk Jin Yun, Rudolph Pienaar, et al.. (2023). Morphological Features of Language Regions in Individuals with Tuberous Sclerosis Complex. Journal of Autism and Developmental Disorders. 54(8). 3155–3175. 1 indexed citations
9.
Madan, Neel, George Graham, Osamu Samura, et al.. (2022). Regional brain development in fetuses with Dandy-Walker malformation: A volumetric fetal brain magnetic resonance imaging study. PLoS ONE. 17(2). e0263535–e0263535. 5 indexed citations
10.
Evald, Lars, Hyuk Jin Yun, Johan Heiberg, et al.. (2021). Abnormal Left‐Hemispheric Sulcal Patterns in Adults With Simple Congenital Heart Defects Repaired in Childhood. Journal of the American Heart Association. 10(7). e018580–e018580. 9 indexed citations
11.
Vasung, Lana, Matthew J. Barkovich, Caitlin K. Rollins, et al.. (2021). Association between Quantitative MR Markers of Cortical Evolving Organization and Gene Expression during Human Prenatal Brain Development. Cerebral Cortex. 31(8). 3610–3621. 13 indexed citations
12.
Yun, Hyuk Jin, Lana Vasung, Tomo Tarui, et al.. (2020). Temporal Patterns of Emergence and Spatial Distribution of Sulcal Pits During Fetal Life. Cerebral Cortex. 30(7). 4257–4268. 17 indexed citations
13.
Morton, Sarah U., David Wypij, Hyuk Jin Yun, et al.. (2019). Abnormal Left-Hemispheric Sulcal Patterns Correlate with Neurodevelopmental Outcomes in Subjects with Single Ventricular Congenital Heart Disease. Cerebral Cortex. 30(2). 476–487. 23 indexed citations
14.
Tarui, Tomo, Kiho Im, Neel Madan, et al.. (2019). Quantitative MRI Analyses of Regional Brain Growth in Living Fetuses with Down Syndrome. Cerebral Cortex. 30(1). 382–390. 37 indexed citations
15.
Ahtam, Banu, et al.. (2018). Altered structural brain connectivity involving the dorsal and ventral language pathways in 16p11.2 deletion syndrome. Brain Imaging and Behavior. 13(2). 430–445. 14 indexed citations
16.
Ortinau, Cynthia M., Caitlin K. Rollins, Ali Gholipour, et al.. (2018). Early-Emerging Sulcal Patterns Are Atypical in Fetuses with Congenital Heart Disease. Cerebral Cortex. 29(8). 3605–3616. 51 indexed citations
17.
Bae, Byoung-Il, Ian Tietjen, Kutay Deniz Atabay, et al.. (2014). Evolutionarily Dynamic Alternative Splicing of GPR56 Regulates Regional Cerebral Cortical Patterning. Science. 343(6172). 764–768. 145 indexed citations
18.
Yang, Jin‐Ju, Uicheul Yoon, Kiho Im, et al.. (2011). Prediction of Human Intelligence using Morphometric Characteristics of Cerebral Cortex. Lecture notes in computer science. 2193(1). 428–432. 1 indexed citations
19.
Kim, Geon Ha, et al.. (2009). T1-Axial Medial Temporal Atrophy Visual Rating: A Comparable Study with Schelten’s T1-Coronal Visual Rating. Dementia and Neurocognitive Disorders. 8(1). 37–44. 3 indexed citations
20.
Im, Kiho, Min-Joo Lee, Yong‐Wook Shin, et al.. (2006). Gender difference analysis of cortical thickness in healthy young adults with surface-based methods. NeuroImage. 31(1). 31–38. 194 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.

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