Lisa Willats

422 total citations
8 papers, 317 citations indexed

About

Lisa Willats is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Lisa Willats has authored 8 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiology, Nuclear Medicine and Imaging, 2 papers in Cognitive Neuroscience and 1 paper in Pulmonary and Respiratory Medicine. Recurrent topics in Lisa Willats's work include Advanced MRI Techniques and Applications (8 papers), MRI in cancer diagnosis (6 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). Lisa Willats is often cited by papers focused on Advanced MRI Techniques and Applications (8 papers), MRI in cancer diagnosis (6 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). Lisa Willats collaborates with scholars based in Australia, United Kingdom and India. Lisa Willats's co-authors include Fernando Calamante, Alan Connelly, David G. Gadian, Robert E. Smith, Jacques‐Donald Tournier, David Raffelt, Sören Christensen, Geoffrey A. Donnan, Richard A. J. Masterton and Henry Ma and has published in prestigious journals such as NeuroImage, Stroke and Magnetic Resonance in Medicine.

In The Last Decade

Lisa Willats

8 papers receiving 307 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lisa Willats Australia	8	283	51	45	33	25	8	317
Vivien Tóth Germany	8	186 0.7×	39 0.8×	36 0.8×	53 1.6×	18 0.7×	11	313
T Hackländer Germany	10	285 1.0×	33 0.6×	37 0.8×	42 1.3×	37 1.5×	31	401
Moss Zhao United States	10	190 0.7×	39 0.8×	30 0.7×	79 2.4×	45 1.8×	23	271
Louise Gyldensted Denmark	4	251 0.9×	30 0.6×	77 1.7×	69 2.1×	62 2.5×	9	359
Kathleen Donahue United States	8	98 0.3×	57 1.1×	78 1.7×	47 1.4×	28 1.1×	14	236
Ty Cashen United States	10	230 0.8×	14 0.3×	58 1.3×	64 1.9×	113 4.5×	20	360
Akio Komatani Japan	8	236 0.8×	39 0.8×	42 0.9×	45 1.4×	38 1.5×	18	392
Liesbeth Geerts Netherlands	10	191 0.7×	25 0.5×	26 0.6×	75 2.3×	20 0.8×	11	354
Adam Kenji Yamamoto United Kingdom	8	114 0.4×	31 0.6×	52 1.2×	21 0.6×	60 2.4×	13	411
Patricia Clement Belgium	6	104 0.4×	33 0.6×	9 0.2×	30 0.9×	17 0.7×	12	148

Countries citing papers authored by Lisa Willats

Since Specialization

Citations

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

Fields of papers citing papers by Lisa Willats

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lisa Willats

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

All Works

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8 of 8 papers shown

1.

Calamante, Fernando, Richard A. J. Masterton, Jacques‐Donald Tournier, et al.. (2013). Track-weighted functional connectivity (TW-FC): A tool for characterizing the structural–functional connections in the brain. NeuroImage. 70. 199–210. 34 indexed citations

2.

Willats, Lisa, David Raffelt, Robert E. Smith, et al.. (2013). Quantification of track-weighted imaging (TWI): Characterisation of within-subject reproducibility and between-subject variability. NeuroImage. 87. 18–31. 26 indexed citations

3.

Willats, Lisa & Fernando Calamante. (2012). The 39 steps: evading error and deciphering the secrets for accurate dynamic susceptibility contrast MRI. NMR in Biomedicine. 26(8). 913–931. 94 indexed citations

4.

Willats, Lisa, Alan Connelly, Sören Christensen, et al.. (2012). The Role of Bolus Delay and Dispersion in Predictor Models for Stroke. Stroke. 43(4). 1025–1031. 15 indexed citations

5.

Willats, Lisa, Sören Christensen, Henry Ma, et al.. (2011). Validating a Local Arterial Input Function Method for Improved Perfusion Quantification in Stroke. Journal of Cerebral Blood Flow & Metabolism. 31(11). 2189–2198. 26 indexed citations

6.

Willats, Lisa, Alan Connelly, & Fernando Calamante. (2008). Minimising the effects of bolus dispersion in bolus‐tracking MRI. NMR in Biomedicine. 21(10). 1126–1137. 20 indexed citations

7.

Calamante, Fernando, Lisa Willats, David G. Gadian, & Alan Connelly. (2006). Bolus delay and dispersion in perfusion MRI: Implications for tissue predictor models in stroke. Magnetic Resonance in Medicine. 55(5). 1180–1185. 60 indexed citations

8.

Willats, Lisa, Alan Connelly, & Fernando Calamante. (2006). Improved deconvolution of perfusion MRI data in the presence of bolus delay and dispersion. Magnetic Resonance in Medicine. 56(1). 146–156. 42 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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