J M Brady

4.2k total citations · 2 hit papers
21 papers, 3.3k citations indexed

About

J M Brady is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Oncology. According to data from OpenAlex, J M Brady has authored 21 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Oncology. Recurrent topics in J M Brady's work include Medical Image Segmentation Techniques (5 papers), AI in cancer detection (3 papers) and Advanced MRI Techniques and Applications (3 papers). J M Brady is often cited by papers focused on Medical Image Segmentation Techniques (5 papers), AI in cancer detection (3 papers) and Advanced MRI Techniques and Applications (3 papers). J M Brady collaborates with scholars based in United Kingdom, United States and Ireland. J M Brady's co-authors include Timothy E.J. Behrens, Paul M. Matthews, Stephen M. Smith, Heidi Johansen‐Berg, Stuart Clare, Mark W. Woolrich, Rita G. Nunes, Mark Jenkinson, Ivana Drobnjak and Matthew F. S. Rushworth and has published in prestigious journals such as Proceedings of the National Academy of Sciences, International Journal of Radiation Oncology*Biology*Physics and Magnetic Resonance in Medicine.

In The Last Decade

J M Brady

21 papers receiving 3.2k citations

Hit Papers

Characterization and propagation of uncertainty in diffus... 2003 2026 2010 2018 2003 2004 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J M Brady United Kingdom 11 2.5k 1.6k 434 374 274 21 3.3k
Robert E. Smith Australia 12 2.7k 1.1× 1.9k 1.2× 607 1.4× 364 1.0× 343 1.3× 18 3.8k
Alex J. de Crespigny United States 18 2.1k 0.9× 1.1k 0.7× 460 1.1× 321 0.9× 221 0.8× 28 3.0k
Kazi Akhter United States 9 2.1k 0.9× 1.1k 0.7× 516 1.2× 359 1.0× 495 1.8× 9 2.8k
Chun‐Hung Yeh Taiwan 15 2.3k 0.9× 1.3k 0.8× 583 1.3× 280 0.7× 261 1.0× 38 3.0k
David Raffelt Australia 17 2.8k 1.2× 1.3k 0.8× 771 1.8× 470 1.3× 505 1.8× 24 3.6k
Jeffrey Duda United States 18 2.8k 1.2× 1.2k 0.8× 835 1.9× 353 0.9× 387 1.4× 44 4.0k
Lidia M. Nagae‐Poetscher United States 11 1.8k 0.7× 768 0.5× 472 1.1× 263 0.7× 332 1.2× 11 2.3k
Philip A. Boulby United Kingdom 23 2.5k 1.0× 1.9k 1.2× 835 1.9× 467 1.2× 982 3.6× 30 3.9k
Daan Christiaens United Kingdom 17 2.6k 1.1× 1.3k 0.8× 792 1.8× 345 0.9× 307 1.1× 41 3.6k
Rita G. Nunes Portugal 23 3.2k 1.3× 1.6k 1.0× 862 2.0× 709 1.9× 340 1.2× 84 4.5k

Countries citing papers authored by J M Brady

Since Specialization
Citations

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

Fields of papers citing papers by J M Brady

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J M Brady. 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 J M Brady. The network helps show where J M Brady may publish in the future.

Co-authorship network of co-authors of J M Brady

This figure shows the co-authorship network connecting the top 25 collaborators of J M Brady. A scholar is included among the top collaborators of J M Brady 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 J M Brady. J M Brady 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
1.
French, John, et al.. (2015). Each Cancer Journey Begins With One Shared Step: Patient Engagement and Radiation Therapy. International Journal of Radiation Oncology*Biology*Physics. 93(3). E502–E503. 2 indexed citations
2.
Noble, J. Alison, et al.. (2007). Adaptive non-rigid registration of real time 3D ultrasound to cardiovascular MR images. Lecture notes in computer science. 50–61. 14 indexed citations
3.
Zhang, Weiwei, J. Alison Noble, & J M Brady. (2007). Adaptive Non-rigid Registration of Real Time 3D Ultrasound to Cardiovascular MR Images. Lecture notes in computer science. 20. 50–61. 16 indexed citations
4.
Jirotka, Marina, Andrew Simpson, Ralph Highnam, et al.. (2005). Digital Mammography: A World without Film?. Methods of Information in Medicine. 44(2). 168–171. 7 indexed citations
5.
Behrenbruch, Christian, et al.. (2004). Image filtering techniques for medical image post-processing: an overview. British Journal of Radiology. 77(suppl_2). S126–S132. 29 indexed citations
6.
Behrenbruch, Christian, Kostas Marias, Paul Armitage, et al.. (2004). Fusion of contrast-enhanced breast MR and mammographic imaging data. British Journal of Radiology. 77(suppl_2). S201–S208. 13 indexed citations
7.
Johansen‐Berg, Heidi, Timothy E.J. Behrens, Matthew D. Robson, et al.. (2004). Changes in connectivity profiles define functionally distinct regions in human medial frontal cortex. Proceedings of the National Academy of Sciences. 101(36). 13335–13340. 539 indexed citations breakdown →
8.
Behrens, Timothy E.J., Mark W. Woolrich, Mark Jenkinson, et al.. (2003). Characterization and propagation of uncertainty in diffusion‐weighted MR imaging. Magnetic Resonance in Medicine. 50(5). 1077–1088. 2444 indexed citations breakdown →
9.
Brady, J M, et al.. (2002). Nonrigid registration of 3-D free-hand ultrasound images of the breast. IEEE Transactions on Medical Imaging. 21(4). 405–412. 50 indexed citations
10.
Highnam, Ralph, J M Brady, & Ruth English. (2001). Simulating disease in mammography. 727–731. 2 indexed citations
11.
Taylor, Chris, et al.. (1997). The detection of stellate lesions in digital mammography. Research Explorer (The University of Manchester). 6 indexed citations
12.
Highnam, Ralph, J M Brady, & B. J. Shepstone. (1996). Removing the anti-scatter grid in mammography. 1119. 459–462. 1 indexed citations
13.
Highnam, Ralph, J M Brady, & B. J. Shepstone. (1996). A quantitative feature to aid diagnosis in mammography. 1119. 201–206. 4 indexed citations
14.
Brady, J M, et al.. (1994). Interference Due to Lipaemia in Routine Photometric Analysis—Survey of an Underrated Problem. Annals of Clinical Biochemistry International Journal of Laboratory Medicine. 31(3). 281–288. 16 indexed citations
15.
Ashraf, Mohd, et al.. (1994). Ifosfamide nephrotoxicity in paediatric cancer patients. European Journal of Pediatrics. 153(2). 90–94. 28 indexed citations
16.
Ashraf, Mohd, et al.. (1994). Ifosfamide nephrotoxicity in paediatric cancer patients. European Journal of Pediatrics. 153(2). 90–94. 2 indexed citations
17.
Brady, J M, et al.. (1989). Scanning electron microscopy of submandibular sialoliths: a preliminary report.. Dentomaxillofacial Radiology. 18(1). 42–44. 8 indexed citations
18.
Lorton, Lewis & J M Brady. (1981). Criteria for successful composite resin restorations.. PubMed. 29(3). 234–6. 3 indexed citations
19.
Rió, Carlos E. del, et al.. (1975). Postdebridement retention of endodontic reagents: A quantitative measurement with radioactive isotope. Journal of Endodontics. 1(9). 298–299. 16 indexed citations
20.
Brady, J M & D E Cutright. (1971). A new technique of measuring blood vessel volume in bone applied to the mandible and humerus of the rat. The Anatomical Record. 170(2). 143–146. 6 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026