Mahbubunnabi Tamal

446 total citations
29 papers, 278 citations indexed

About

Mahbubunnabi Tamal is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Mahbubunnabi Tamal has authored 29 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Biomedical Engineering and 7 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Mahbubunnabi Tamal's work include Medical Imaging Techniques and Applications (18 papers), Advanced X-ray and CT Imaging (14 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Mahbubunnabi Tamal is often cited by papers focused on Medical Imaging Techniques and Applications (18 papers), Advanced X-ray and CT Imaging (14 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Mahbubunnabi Tamal collaborates with scholars based in Saudi Arabia, United Kingdom and Malaysia. Mahbubunnabi Tamal's co-authors include Rafidah Zainon, Waleed Albaker, Ibraheem Al‐Naib, Andrew J. Reader, P. J. Julyan, D. L. Hastings, Paweł Markiewicz, Corinne Faivre‐Finn, Ben Taylor and Fiona Blackhall and has published in prestigious journals such as Journal of Clinical Oncology, Expert Systems with Applications and Sensors.

In The Last Decade

Mahbubunnabi Tamal

25 papers receiving 273 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mahbubunnabi Tamal Saudi Arabia 8 164 98 45 35 32 29 278
Limin Zhang China 12 332 2.0× 390 4.0× 29 0.6× 16 0.5× 47 1.5× 73 533
Yu-Ching Ni Taiwan 8 133 0.8× 117 1.2× 60 1.3× 56 1.6× 14 0.4× 25 302
Marian Axente United States 8 195 1.2× 125 1.3× 59 1.3× 73 2.1× 8 0.3× 22 287
Roee S. Lazebnik United States 11 145 0.9× 119 1.2× 39 0.9× 8 0.2× 20 0.6× 20 317
Parinaz Mehnati Iran 12 226 1.4× 133 1.4× 160 3.6× 99 2.8× 10 0.3× 48 422
Anaïs Leproux United States 10 285 1.7× 243 2.5× 33 0.7× 3 0.1× 36 1.1× 24 383
Jianfeng Wang China 8 91 0.6× 256 2.6× 29 0.6× 4 0.1× 111 3.5× 28 391
Roxana Vlad Canada 9 265 1.6× 267 2.7× 26 0.6× 15 0.4× 66 2.1× 12 428
Matt Holbrook United States 12 221 1.3× 176 1.8× 55 1.2× 21 0.6× 9 0.3× 27 288

Countries citing papers authored by Mahbubunnabi Tamal

Since Specialization
Citations

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

Fields of papers citing papers by Mahbubunnabi Tamal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mahbubunnabi Tamal

This figure shows the co-authorship network connecting the top 25 collaborators of Mahbubunnabi Tamal. A scholar is included among the top collaborators of Mahbubunnabi Tamal 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 Mahbubunnabi Tamal. Mahbubunnabi Tamal 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.
Tamal, Mahbubunnabi, et al.. (2025). Dynamic time warping for enhanced fNIRS-based motor assessment during lower limb kinematics. Informatics in Medicine Unlocked. 58. 101684–101684.
2.
Tamal, Mahbubunnabi, et al.. (2024). Radiomic features based automatic classification of CT lung findings for COVID-19 patients. Biomedical Physics & Engineering Express. 11(1). 15012–15012.
3.
Zainon, Rafidah, et al.. (2024). Assessing tissue differentiation capabilities in X-ray imaging through cadmium zinc telluride (CZT) photon counting detectors.. Radiation Physics and Chemistry. 222. 111867–111867.
4.
Tamal, Mahbubunnabi, et al.. (2023). A review on optimization of Wilms tumour management using radiomics. BJR|Open. 6(1). tzae034–tzae034.
5.
Zainon, Rafidah, et al.. (2022). A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease management. Insights into Imaging. 13(1). 22–22. 20 indexed citations
6.
Zainon, Rafidah, et al.. (2022). Correction: A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease management. Insights into Imaging. 13(1). 32–32. 2 indexed citations
7.
Tamal, Mahbubunnabi, et al.. (2022). Synchrotron X-ray Radiation (SXR) in Medical Imaging: Current Status and Future Prospects. Applied Sciences. 12(8). 3790–3790. 6 indexed citations
8.
Tamal, Mahbubunnabi, et al.. (2021). Sciatic nerve excursion during neural mobilization with ankle movement using dynamic ultrasound imaging: a cross-sectional study. Journal of Ultrasound. 25(2). 241–249. 4 indexed citations
9.
Tamal, Mahbubunnabi, et al.. (2021). An integrated framework with machine learning and radiomics for accurate and rapid early diagnosis of COVID-19 from Chest X-ray. Expert Systems with Applications. 180. 115152–115152. 26 indexed citations
10.
Tamal, Mahbubunnabi, et al.. (2021). A Review of Non-Invasive Optical Systems for Continuous Blood Glucose Monitoring. Sensors. 21(20). 6820–6820. 66 indexed citations
11.
Tamal, Mahbubunnabi. (2020). Intensity threshold based solid tumour segmentation method for Positron Emission Tomography (PET) images: A review. Heliyon. 6(10). e05267–e05267. 22 indexed citations
12.
13.
Koh, P., Ben Taylor, Mahbubunnabi Tamal, et al.. (2014). Early reduction in tumour [18F]fluorothymidine (FLT) uptake in patients with non-small cell lung cancer (NSCLC) treated with radiotherapy alone. European Journal of Nuclear Medicine and Molecular Imaging. 41(4). 682–693. 36 indexed citations
14.
Lamarca, Ángela, Prakash Manoharan, Marie‐Claude Asselin, et al.. (2013). Pilot, proof-of-concept studies for determining the feasibility of the use of FLT-PET in patients with pancreatic adenocarcinoma.. Journal of Clinical Oncology. 31(15_suppl). TPS4146–TPS4146. 2 indexed citations
15.
16.
Markiewicz, Paweł, Mahbubunnabi Tamal, P. J. Julyan, D. L. Hastings, & Andrew J. Reader. (2007). High accuracy multiple scatter modelling for 3D whole body PET. Physics in Medicine and Biology. 52(3). 829–847. 18 indexed citations
17.
Markiewicz, Paweł, Andrew J. Reader, Mahbubunnabi Tamal, P. J. Julyan, & D. L. Hastings. (2006). An Advanced Analytic Method Incorporating the Geometric Properties of Scanner and Radiation Emissions into the System Model for the True Component of 3D PET Data. 4. 2310–2314. 7 indexed citations
18.
Tamal, Mahbubunnabi, Paweł Markiewicz, P. J. Julyan, D. L. Hastings, & Andrew J. Reader. (2006). Impact of Scatter Modeling Error on 3D Maximum Likelihood Reconstruction in PET. 2006 IEEE Nuclear Science Symposium Conference Record. 3154–3158. 1 indexed citations
19.
Markiewicz, Paweł, Andrew J. Reader, Mahbubunnabi Tamal, P. J. Julyan, & D. L. Hastings. (2005). Towards an accurate voxel-based analytic unified scatter and attenuation system model for 3D PET. IEEE Symposium Conference Record Nuclear Science 2004.. 4. 2199–2203. 1 indexed citations
20.
Tamal, Mahbubunnabi, Andrew J. Reader, Paweł Markiewicz, D. L. Hastings, & P. J. Julyan. (2004). Noise Properties of Four Strategies for Incorporation of Attenuation and Scatter Information in 3D Whole Body PET. Research Explorer (The University of Manchester). 2840–2844. 2 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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