Martin Lillholm

2.4k total citations · 1 hit paper
49 papers, 1.4k citations indexed

About

Martin Lillholm is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Martin Lillholm has authored 49 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 12 papers in Pulmonary and Respiratory Medicine and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Martin Lillholm's work include AI in cancer detection (16 papers), Digital Radiography and Breast Imaging (12 papers) and Global Cancer Incidence and Screening (10 papers). Martin Lillholm is often cited by papers focused on AI in cancer detection (16 papers), Digital Radiography and Breast Imaging (12 papers) and Global Cancer Incidence and Screening (10 papers). Martin Lillholm collaborates with scholars based in Denmark, Netherlands and United Kingdom. Martin Lillholm's co-authors include Mads Nielsen, Erik B. Dam, Martín Koch, Nico Karssemeijer, Elsebeth Lynge, Christian Igel, My von Euler‐Chelpin, Lewis D. Griffin, Kersten Petersen and Michiel Kallenberg and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Radiology and Magnetic Resonance in Medicine.

In The Last Decade

Martin Lillholm

48 papers receiving 1.4k 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.

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring

2016 319 citations Michiel Kallenberg, Mads Nielsen et al. IEEE Transactions on Medical Imaging profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Martin Lillholm Denmark	17	572	479	284	281	210	49	1.4k
Parvin Mousavi Canada	27	624 1.1×	741 1.5×	422 1.5×	504 1.8×	110 0.5×	199	2.5k
Diana Mateus France	20	431 0.8×	492 1.0×	122 0.4×	683 2.4×	112 0.5×	63	1.5k
Yu Zhu China	21	290 0.5×	224 0.5×	135 0.5×	707 2.5×	102 0.5×	132	1.7k
Alexander Schlaefer Germany	22	233 0.4×	659 1.4×	396 1.4×	202 0.7×	137 0.7×	175	1.6k
Miguel Á. González Ballester Spain	27	336 0.6×	629 1.3×	240 0.8×	522 1.9×	44 0.2×	165	2.4k
Evangelia I. Zacharaki Greece	24	499 0.9×	1.4k 2.8×	340 1.2×	791 2.8×	190 0.9×	88	2.8k
Deepak Ranjan Nayak India	26	908 1.6×	760 1.6×	97 0.3×	723 2.6×	106 0.5×	74	2.0k
Christian Desrosiers Canada	25	748 1.3×	1.1k 2.3×	233 0.8×	991 3.5×	115 0.5×	144	2.7k
María A. Zuluaga France	19	988 1.7×	705 1.5×	151 0.5×	818 2.9×	88 0.4×	76	2.4k
Yao Lu China	24	671 1.2×	956 2.0×	501 1.8×	519 1.8×	130 0.6×	161	2.2k

Countries citing papers authored by Martin Lillholm

Since Specialization

Citations

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

Fields of papers citing papers by Martin Lillholm

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Lillholm

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

Napolitano, George, Martin Lillholm, Rikke Rass Winkel, et al.. (2024). Introduction of one-view tomosynthesis in population-based mammography screening: Impact on detection rate, interval cancer rate and false-positive rate. Journal of Medical Screening. 32(1). 28–34.

Lauritzen, Andreas D., Martin Lillholm, Elsebeth Lynge, et al.. (2024). Early Indicators of the Impact of Using AI in Mammography Screening for Breast Cancer. Radiology. 311(3). e232479–e232479. 32 indexed citations

Napolitano, George, Andreas D. Lauritzen, Elsebeth Lynge, et al.. (2024). Clinical Significance of Combined Density and Deep-Learning-Based Texture Analysis for Stratifying the Risk of Short-Term and Long-Term Breast Cancer in Screening. Diagnostics. 14(16). 1823–1823. 1 indexed citations

Lauritzen, Andreas D., My von Euler‐Chelpin, Elsebeth Lynge, et al.. (2023). Assessing Breast Cancer Risk by Combining AI for Lesion Detection and Mammographic Texture. Radiology. 308(2). e230227–e230227. 16 indexed citations

Lauritzen, Andreas D., My von Euler‐Chelpin, Elsebeth Lynge, et al.. (2023). Robust cross-vendor mammographic texture models using augmentation-based domain adaptation for long-term breast cancer risk. Journal of Medical Imaging. 10(5). 54003–54003. 2 indexed citations

Lauritzen, Andreas D., Alejandro Rodríguez‐Ruiz, My von Euler‐Chelpin, et al.. (2022). An Artificial Intelligence–based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload. Radiology. 304(1). 41–49. 102 indexed citations

Vejborg, Ilse, Elsebeth Lynge, Martin Lillholm, et al.. (2020). Impact of adding breast density to breast cancer risk models: A systematic review. European Journal of Radiology. 127. 109019–109019. 44 indexed citations

Euler‐Chelpin, My von, Martin Lillholm, Ilse Vejborg, Mads Nielsen, & Elsebeth Lynge. (2019). Sensitivity of screening mammography by density and texture: a cohort study from a population-based screening program in Denmark. Breast Cancer Research. 21(1). 111–111. 64 indexed citations

Euler‐Chelpin, My von, Martin Lillholm, George Napolitano, et al.. (2018). Screening mammography: benefit of double reading by breast density. Breast Cancer Research and Treatment. 171(3). 767–776. 25 indexed citations

10.

Wanders, Johanna O. P., Carla H. van Gils, Nico Karssemeijer, et al.. (2018). The combined effect of mammographic texture and density on breast cancer risk: a cohort study. Breast Cancer Research. 20(1). 36–36. 32 indexed citations

11.

Winkel, Rikke Rass, My von Euler‐Chelpin, Elsebeth Lynge, et al.. (2017). Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: A case control study. Cancer Epidemiology. 49. 53–60. 9 indexed citations

12.

Sørensen, Lauge, et al.. (2016). Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry. NeuroImage Clinical. 13. 470–482. 122 indexed citations

13.

Lillholm, Martin, et al.. (2013). On Subregional Analysis of Cartilage Loss from Knee MRI. Cartilage. 4(2). 121–130. 10 indexed citations

14.

Tummala, Sudhakar, Mads Nielsen, Martin Lillholm, Claus Christiansen, & Erik B. Dam. (2012). Automatic Quantification of Tibio-Femoral Contact Area and Congruity. IEEE Transactions on Medical Imaging. 31(7). 1404–1412. 11 indexed citations

15.

Lillholm, Martin, et al.. (2012). Automatic analysis of trabecular bone structure from knee MRI. Computers in Biology and Medicine. 42(7). 735–742. 4 indexed citations

16.

Crimi, Alessandro, Martin Lillholm, Mads Nielsen, et al.. (2011). Maximum a Posteriori Estimation of Linear Shape Variation With Application to Vertebra and Cartilage Modeling. IEEE Transactions on Medical Imaging. 30(8). 1514–1526. 3 indexed citations

17.

Lillholm, Martin, et al.. (2008). Classifying local image symmetry using a co-localised family of linear filters. Perception. 37. 122–122. 2 indexed citations

18.

Lillholm, Martin, Mads Nielsen, & Lewis D. Griffin. (2003). Feature-Based Image Analysis. International Journal of Computer Vision. 52(2-3). 73–95. 26 indexed citations

19.

Griffin, Lewis D., Martin Lillholm, & Mads Nielsen. (2003). Natural image profiles are most likely to be step edges. Vision Research. 44(4). 407–421. 15 indexed citations

20.

Dam, Erik B., Martín Koch, & Martin Lillholm. (2000). Quaternions, Interpolation and Animation. Research at the University of Copenhagen (University of Copenhagen). 200 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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