Lin‐Ching Chang

2.9k total citations · 1 hit paper
61 papers, 1.9k citations indexed

About

Lin‐Ching Chang is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Lin‐Ching Chang has authored 61 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Computer Vision and Pattern Recognition and 8 papers in Biomedical Engineering. Recurrent topics in Lin‐Ching Chang's work include Advanced Neuroimaging Techniques and Applications (18 papers), Advanced MRI Techniques and Applications (16 papers) and Medical Image Segmentation Techniques (7 papers). Lin‐Ching Chang is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (18 papers), Advanced MRI Techniques and Applications (16 papers) and Medical Image Segmentation Techniques (7 papers). Lin‐Ching Chang collaborates with scholars based in United States, United Kingdom and Canada. Lin‐Ching Chang's co-authors include Carlo Pierpaoli, Derek K. Jones, Cheng Guan Koay, Peter J. Basser, Lindsay Walker, Vy Bui, Thanh Nguyen, John D. Carew, Van Lam and Christopher B. Raub and has published in prestigious journals such as Advanced Functional Materials, NeuroImage and Magnetic Resonance in Medicine.

In The Last Decade

Lin‐Ching Chang

56 papers receiving 1.9k 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.

RESTORE: Robust estimation of tensors by outlier rejection

2005 513 citations Lin‐Ching Chang, Derek K. Jones et al. Magnetic Resonance in Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lin‐Ching Chang United States	20	1.2k	351	298	187	174	61	1.9k
Alexander Egan United States	5	1.9k 1.6×	378 1.1×	1.1k 3.7×	655 3.5×	71 0.4×	6	4.0k
Christophe Lenglet United States	29	2.7k 2.2×	452 1.3×	1.1k 3.8×	256 1.4×	54 0.3×	101	3.5k
Lewis D. Griffin United Kingdom	28	559 0.5×	108 0.3×	351 1.2×	866 4.6×	103 0.6×	102	2.6k
Stephen J. Blackband United States	35	2.6k 2.2×	304 0.9×	301 1.0×	159 0.9×	171 1.0×	112	3.9k
Sridar Narayanan Canada	48	2.0k 1.7×	212 0.6×	466 1.6×	201 1.1×	34 0.2×	136	6.5k
Ming‐Chung Chou Taiwan	17	545 0.4×	95 0.3×	150 0.5×	69 0.4×	72 0.4×	68	1.0k
Declan Chard United Kingdom	45	2.4k 2.0×	164 0.5×	538 1.8×	119 0.6×	30 0.2×	149	6.9k
Carl‐Fredrik Westin United States	26	2.7k 2.2×	434 1.2×	715 2.4×	183 1.0×	22 0.1×	69	3.2k
Alessandra Retico Italy	23	702 0.6×	61 0.2×	497 1.7×	212 1.1×	57 0.3×	118	1.7k
Justin P. Haldar United States	30	3.0k 2.5×	98 0.3×	353 1.2×	412 2.2×	345 2.0×	123	4.0k

Countries citing papers authored by Lin‐Ching Chang

Since Specialization

Citations

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

Fields of papers citing papers by Lin‐Ching Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lin‐Ching Chang. 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 Lin‐Ching Chang. The network helps show where Lin‐Ching Chang may publish in the future.

Co-authorship network of co-authors of Lin‐Ching Chang

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

All Works

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20 of 20 papers shown

Benovoy, Mitchel, Lin‐Ching Chang, David Corcoran, et al.. (2021). Automated Segmental Analysis of Fully Quantitative Myocardial Blood Flow Maps by First-Pass Perfusion Cardiovascular Magnetic Resonance. IEEE Access. 9. 52796–52811. 17 indexed citations

Chang, Lin‐Ching, et al.. (2021). Comparative Study of 3D Point Cloud Compression Methods. 2021 IEEE International Conference on Big Data (Big Data). 6 indexed citations

Chang, Lin‐Ching, et al.. (2020). A 5-min Cognitive Task With Deep Learning Accurately Detects Early Alzheimer's Disease. Frontiers in Aging Neuroscience. 12. 603179–603179. 16 indexed citations

Bui, Vy, Li‐Yueh Hsu, Sujata M. Shanbhag, et al.. (2020). Improving multi-atlas cardiac structure segmentation of computed tomography angiography: A performance evaluation based on a heterogeneous dataset. Computers in Biology and Medicine. 125. 104019–104019. 9 indexed citations

Bui, Vy, Sujata M. Shanbhag, W. Patricia Bandettini, et al.. (2020). Simultaneous Multi-Structure Segmentation of the Heart and Peripheral Tissues in Contrast Enhanced Cardiac Computed Tomography Angiography. IEEE Access. 8. 16187–16202. 7 indexed citations

Thai, Anh, et al.. (2019). Using Deep Convolutional Neural Network for Mouse Brain Segmentation in DT-MRI. 14. 6229–6231. 2 indexed citations

Liang, Xiaomeng, Nanxi Lu, Lin‐Ching Chang, Thanh H. Nguyen, & Arash Massoudieh. (2018). Evaluation of bacterial run and tumble motility parameters through trajectory analysis. Journal of Contaminant Hydrology. 211. 26–38. 9 indexed citations

Benovoy, Mitchel, et al.. (2016). Evaluation of an automated method for arterial input function detection for first-pass myocardial perfusion cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance. 18(1). 17–17. 35 indexed citations

Walker, Lindsay, Lin‐Ching Chang, Amritha Nayak, et al.. (2015). The diffusion tensor imaging (DTI) component of the NIH MRI study of normal brain development (PedsDTI). NeuroImage. 124(Pt B). 1125–1130. 33 indexed citations

10.

Chang, Lin‐Ching, et al.. (2014). Walking, balance, and functional status: Comparison between perceived and actual assessments among ambulating persons post stroke in the community. 10(5). 247–255. 1 indexed citations

11.

Glancy, Brian, et al.. (2014). Use of independent component analysis to improve signal‐to‐noise ratio in multi‐probe fluorescence microscopy. Journal of Microscopy. 256(2). 133–144. 5 indexed citations

12.

Hsu, Shao‐Yiu, et al.. (2014). Pore-Scale Study of the Effect of the Saturation History on Fluid Saturation and Relative Permeability of Three-Fluid Flow in Porous Media. AGU Fall Meeting Abstracts. 2014. 1 indexed citations

13.

Chang, Lin‐Ching, Lindsay Walker, & Carlo Pierpaoli. (2012). Informed RESTORE: A method for robust estimation of diffusion tensor from low redundancy datasets in the presence of physiological noise artifacts. Magnetic Resonance in Medicine. 68(5). 1654–1663. 93 indexed citations

14.

Walker, Lindsay, Lin‐Ching Chang, Cheng Guan Koay, et al.. (2010). Effects of physiological noise in population analysis of diffusion tensor MRI data. NeuroImage. 54(2). 1168–1177. 55 indexed citations

15.

Chang, Lin‐Ching, Cheng Guan Koay, Peter J. Basser, & Carlo Pierpaoli. (2008). Linear least‐squares method for unbiased estimation of T₁ from SPGR signals. Magnetic Resonance in Medicine. 60(2). 496–501. 57 indexed citations

16.

Koay, Cheng Guan, et al.. (2007). Error Propagation Framework for Diffusion Tensor Imaging via Diffusion Tensor Representations. IEEE Transactions on Medical Imaging. 26(8). 1017–1034. 26 indexed citations

17.

Freidlin, Raisa Z., Evren Özarslan, Michal E. Komlosh, et al.. (2007). Parsimonious Model Selection for Tissue Segmentation and Classification Applications: A Study Using Simulated and Experimental DTI Data. IEEE Transactions on Medical Imaging. 26(11). 1576–1584. 22 indexed citations

18.

Chang, Lin‐Ching, Cheng Guan Koay, Carlo Pierpaoli, & Peter J. Basser. (2006). Variance of estimated DTI‐derived parameters via first‐order perturbation methods. Magnetic Resonance in Medicine. 57(1). 141–149. 34 indexed citations

19.

Koay, Cheng Guan, Lin‐Ching Chang, John D. Carew, Carlo Pierpaoli, & Peter J. Basser. (2006). A unifying theoretical and algorithmic framework for least squares methods of estimation in diffusion tensor imaging. Journal of Magnetic Resonance. 182(1). 115–125. 179 indexed citations

20.

Chang, Lin‐Ching & Chao Yang. (2002). OPTIMIZING THE RULE CURVES FOR MULTI-RESERVOIR OPERATIONS USING A GENETIC ALGORITHM AND HEC-5. 20(1). 59–75. 9 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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