Min Xian

2.2k total citations
59 papers, 1.3k citations indexed

About

Min Xian is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Min Xian has authored 59 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 31 papers in Computer Vision and Pattern Recognition and 12 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Min Xian's work include AI in cancer detection (22 papers), Medical Image Segmentation Techniques (12 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Min Xian is often cited by papers focused on AI in cancer detection (22 papers), Medical Image Segmentation Techniques (12 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Min Xian collaborates with scholars based in United States, China and Malaysia. Min Xian's co-authors include Aleksandar Vakanski, Yingtao Zhang, Heng-Da Cheng, Jianrui Ding, Boyu Zhang, Fei Xu, He Cheng, Xianglong Tang, Chunping Ning and Haotian Wang and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Min Xian

57 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Min Xian United States	18	815	622	500	166	138	59	1.3k
Shuihua Wang United Kingdom	20	502 0.6×	417 0.7×	385 0.8×	185 1.1×	128 0.9×	66	1.4k
Nipon Theera‐Umpon Thailand	20	620 0.8×	572 0.9×	205 0.4×	52 0.3×	133 1.0×	128	1.5k
Xiangbin Liu China	13	293 0.4×	357 0.6×	277 0.6×	116 0.7×	103 0.7×	63	998
Anjan Gudigar India	27	457 0.6×	633 1.0×	952 1.9×	337 2.0×	243 1.8×	58	2.0k
Dhanesh Ramachandram Malaysia	13	397 0.5×	345 0.6×	145 0.3×	46 0.3×	73 0.5×	39	992
Qihang Yu United States	10	405 0.5×	615 1.0×	365 0.7×	94 0.6×	86 0.6×	20	991
Hulin Kuang China	20	141 0.2×	439 0.7×	192 0.4×	168 1.0×	211 1.5×	57	1.1k
Yuting He China	12	348 0.4×	512 0.8×	449 0.9×	125 0.8×	262 1.9×	36	1.3k
Junding Sun China	18	462 0.6×	612 1.0×	320 0.6×	358 2.2×	143 1.0×	90	1.5k

Countries citing papers authored by Min Xian

Since Specialization

Citations

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

Fields of papers citing papers by Min Xian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Xian

This figure shows the co-authorship network connecting the top 25 collaborators of Min Xian. A scholar is included among the top collaborators of Min Xian 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 Min Xian. Min Xian 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

Xian, Min, et al.. (2024). CFR-ICL: Cascade-Forward Refinement with Iterative Click Loss for Interactive Image Segmentation. Proceedings of the AAAI Conference on Artificial Intelligence. 38(5). 5017–5024. 9 indexed citations

Xian, Min, et al.. (2024). Semantic-Aware Adaptive Binary Search for Hard-Label Black-Box Attack. Computers. 13(8). 203–203. 1 indexed citations

Vakanski, Aleksandar, et al.. (2024). Bend-Net: Bending Loss Regularized Multitask Learning Network for Nuclei Segmentation in Histopathology Images. Information. 15(7). 417–417. 1 indexed citations

Vakanski, Aleksandar, et al.. (2024). Uncertainty quantification in multivariable regression for material property prediction with Bayesian neural networks. Scientific Reports. 14(1). 10543–10543. 21 indexed citations

Zhang, Sai, et al.. (2024). Causality Extraction from Nuclear Licensee Event Reports Using a Hybrid Framework. arXiv (Cornell University). 1 indexed citations

Xian, Min, et al.. (2023). Breast Ultrasound Tumor Classification Using a Hybrid Multitask CNN-Transformer Network. Lecture notes in computer science. 14223. 344–353. 7 indexed citations

Capriotti, Luca, et al.. (2023). An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel. Scientific Reports. 13(1). 22275–22275. 2 indexed citations

Wang, Lingtao, et al.. (2023). CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network. 1–5. 53 indexed citations

Xian, Min, et al.. (2023). A Benchmark for Breast Ultrasound Image Classification. SSRN Electronic Journal. 6 indexed citations

10.

Wang, Haotian, Lu Cai, Fidelma Giulia Di Lemma, et al.. (2023). A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel. Scientific Reports. 13(1). 22274–22274. 3 indexed citations

11.

Zhang, Yingtao, Min Xian, Heng-Da Cheng, et al.. (2022). BUSIS: A Benchmark for Breast Ultrasound Image Segmentation. Healthcare. 10(4). 729–729. 49 indexed citations

12.

Shi, Changfa, et al.. (2021). Multi-slice low-rank tensor decomposition based multi-atlas segmentation: Application to automatic pathological liver CT segmentation. Medical Image Analysis. 73. 102152–102152. 13 indexed citations

13.

Wang, Zhe, Chao Fan, & Min Xian. (2021). Application and Evaluation of a Deep Learning Architecture to Urban Tree Canopy Mapping. Remote Sensing. 13(9). 1749–1749. 16 indexed citations

14.

Vakanski, Aleksandar, et al.. (2020). Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images. Ultrasound in Medicine & Biology. 46(10). 2819–2833. 135 indexed citations

15.

Li, Rui, et al.. (2020). Imputation of single‐cell gene expression with an autoencoder neural network. Quantitative Biology. 8(1). 78–94. 41 indexed citations

16.

Wang, Haotian, Min Xian, & Aleksandar Vakanski. (2020). Bending Loss Regularized Network for Nuclei Segmentation in Histopathology Images. PubMed. 2020. 1–5. 24 indexed citations

17.

Liao, Yun, Aleksandar Vakanski, & Min Xian. (2019). A deep learning framework for assessment of quality of rehabilitation exercises. arXiv (Cornell University). 3 indexed citations

18.

Wang, Yangyang, Rongrong Ni, Yao Zhao, & Min Xian. (2018). Watermark Embedding for Direct Binary Searched Halftone Images by Adopting Visual Cryptography. Cmc-computers Materials & Continua. 55(2). 255–265. 3 indexed citations

19.

Yu, Hongkai, Youjie Zhou, Hui Qian, Min Xian, & Song Wang. (2017). Loosecut: Interactive image segmentation with loosely bounded boxes. 3335–3339. 24 indexed citations

20.

Zhang, Yingtao, et al.. (2015). A saliency model for automated tumor detection in breast ultrasound images. 1424–1428. 33 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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