Manoj Mannil

2.0k citations

69 papers · 1.4k indexed · h-index 21

Impact in

Health Informatics top 1%
Radiology, Nuclear Medicine and Imaging top 1%
- Radiomics and Machine Learning in Medical Imaging
- Cardiac Imaging and Diagnostics
- Radiation Dose and Imaging
- Medical Imaging Techniques and Applications
- Advanced MRI Techniques and Applications

Papers in ⓘ

Radiology, Nuclear Medicine and Imaging 45
- Radiomics and Machine Learning in Medical Imaging 25
- Cardiac Imaging and Diagnostics 12
- Advanced MRI Techniques and Applications 10
- Medical Imaging Techniques and Applications 8
- MRI in cancer diagnosis 7
Genetics 18
- Glioma Diagnosis and Treatment 18

Co-authors: Hatem Alkadhi (22 shared papers)Robert Manka (10 shared papers)Jochen von Spiczak (13 shared papers)David Maintz (4 shared papers)Bettina Baeßler (4 shared papers)Roman Guggenberger (7 shared papers)Sabrina Oebel (2 shared papers)Bernhard Schmidt (3 shared papers)
Journals: Scientific Reports (9 papers)Cancers (6 papers)European Journal of Radiology (6 papers)Investigative Radiology (5 papers)European Radiology (4 papers)
Partner nations: Switzerland Germany Netherlands

In The Last Decade

Manoj Mannil

64 papers receiving 1.4k citations

Peers

Countries citing papers authored by Manoj Mannil

Since Specialization

Citations

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

Fields of papers citing papers by Manoj Mannil

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Manoj Mannil, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Manoj Mannil Line = papers co-authored together Manoj Mannil links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Subacute and Chronic Left Ventricular Myocardial Scar: Accuracy of Texture Analysis on Nonenhanced Cine MR Images Radiology ·Bettina Baeßler, Manoj Mannil, Sabrina Oebel, David Maintz, Hatem Alkadhi, Robert Manka	2017	152
2	Texture Analysis and Machine Learning for Detecting Myocardial Infarction in Noncontrast Low-Dose Computed Tomography Investigative Radiology ·Manoj Mannil, Jochen von Spiczak, Robert Manka, Hatem Alkadhi	2018	107
3	Photon-Counting CT Investigative Radiology ·Manoj Mannil, Tilman Hickethier, Jochen von Spiczak, Matthias Baer, André Henning, Madeleine Hertel, Bernhard Schmidt, Thomas Flohr, David Maintz, Hatem Alkadhi	2017	106
4	Texture analysis and machine learning of non-contrast T1-weighted MR images in patients with hypertrophic cardiomyopathy—Preliminary results European Journal of Radiology ·Bettina Baeßler, Manoj Mannil, David Maintz, Hatem Alkadhi, Robert Manka	2018	98
5	Vertebral body insufficiency fractures: detection of vertebrae at risk on standard CT images using texture analysis and machine learning European Radiology ·Urs J. Muehlematter, Manoj Mannil, Anton S. Becker, Kerstin Noëlle Vokinger, Tim Finkenstaedt, Georg Osterhoff, Michael A. Fischer, Roman Guggenberger	2018	94
6	Photon Counting Computed Tomography With Dedicated Sharp Convolution Kernels Investigative Radiology ·Jochen von Spiczak, Manoj Mannil, Benjamin Peters, Tilman Hickethier, Matthias Baer, André Henning, Bernhard Schmidt, Thomas Flohr, Robert Manka, David Maintz, Hatem Alkadhi	2018	67
7	Performance of machine learning algorithms for glioma segmentation of brain MRI: a systematic literature review and meta-analysis European Radiology ·Evi J. van Kempen, Max Post, Manoj Mannil, Richard L. Witkam, Mark ter Laan, Ajay Patel, Frederick J. A. Meijer, Dylan Henssen	2021	49
8	The potential of machine learning to predict postoperative pancreatic fistula based on preoperative, non-contrast-enhanced CT: A proof-of-principle study Surgery ·Patryk Kambakamba, Manoj Mannil, Paola E. Herrera, Philip C. Müller, Christoph Kuemmerli, Michael Linecker, Jochen von Spiczak, Martin Hüllner, Dimitri A. Raptis, Henrik Petrowsky, Pierre–Alain Clavien, Hatem Alkadhi	2019	49
9	Modified Dual-Energy Algorithm for Calcified Plaque Removal Investigative Radiology ·Manoj Mannil, Jaychandran Ramachandran, I. Martini, Susanne Wegener, Bernhard Schmidt, Thomas Flohr, Bernhard Krauß, Antonios Valavanis, Hatem Alkadhi, Sebastian Winklhofer	2017	49
10	Three-Dimensional Texture Analysis with Machine Learning Provides Incremental Predictive Information for Successful Shock Wave Lithotripsy in Patients with Kidney Stones The Journal of Urology ·Manoj Mannil, Jochen von Spiczak, Thomas Hermanns, Cédric Poyet, Hatem Alkadhi, Christian D. Fankhauser	2018	43
11	Amide proton transfer weighted (APTw) imaging based radiomics allows for the differentiation of gliomas from metastases Scientific Reports ·Elisabeth Sartoretti, Thomas Sartoretti, Michael Wyss, Carolin Reischauer, Luuk van Smoorenburg, Christoph A. Binkert, Sabine Sartoretti‐Schefer, Manoj Mannil	2021	36
12	Applicability of radiomics in interstitial lung disease associated with systemic sclerosis: proof of concept European Radiology ·Katharina Martini, Bettina Baeßler, Marta Bogowicz, Christian Blüthgen, Manoj Mannil, Stephanie Tanadini‐Lang, Janine Gote-Schniering, Britta Maurer, Thomas Frauenfelder	2020	35
13	Radiomics for Distinguishing Myocardial Infarction from Myocarditis at Late Gadolinium Enhancement at MRI: Comparison with Subjective Visual Analysis Radiology Cardiothoracic Imaging ·Tommaso Di Noto, Jochen von Spiczak, Manoj Mannil, Elena Gantert, Paolo Soda, Robert Manka, Hatem Alkadhi	2019	34
14	Texture analysis of paraspinal musculature in MRI of the lumbar spine: analysis of the lumbar stenosis outcome study (LSOS) data Skeletal Radiology ·Manoj Mannil, Jakob M. Burgstaller, Arjun Thanabalasingam, Sebastian Winklhofer, Michael Betz, Ulrike Held, Roman Guggenberger	2018	31
15	Accuracy of Machine Learning Algorithms for the Classification of Molecular Features of Gliomas on MRI: A Systematic Literature Review and Meta-Analysis Cancers ·Evi J. van Kempen, Max Post, Manoj Mannil, Benno Küsters, Mark ter Laan, Frederick J. A. Meijer, Dylan Henssen	2021	26
16	Qualitative versus quantitative lumbar spinal stenosis grading by machine learning supported texture analysis—Experience from the LSOS study cohort European Journal of Radiology ·Florian A. Huber, Shanon Stutz, I. Martini, Manoj Mannil, Anton S. Becker, Sebastian Winklhofer, Jakob M. Burgstaller, Roman Guggenberger	2019	26
17	Correlation of texture analysis of paraspinal musculature on MRI with different clinical endpoints: Lumbar Stenosis Outcome Study (LSOS) European Radiology ·Manoj Mannil, Jakob M. Burgstaller, Ulrike Held, Mazda Farshad, Roman Guggenberger	2018	25
18	Prediction of successful shock wave lithotripsy with CT: a phantom study using texture analysis Abdominal Radiology ·Manoj Mannil, Jochen von Spiczak, Thomas Hermanns, Hatem Alkadhi, Christian D. Fankhauser	2017	24
19	Testing the applicability and performance of Auto ML for potential applications in diagnostic neuroradiology Scientific Reports ·Manfred Musigmann, Burak Han Akkurt, Hermann Krähling, Nabila Gala Nacul, Luca Remonda, Thomas Sartoretti, Dylan Henssen, Benjamin Brokinkel, Walter Stummer, Walter Heindel, Manoj Mannil	2022	23
20	Deep learning based detection of intracranial aneurysms on digital subtraction angiography: A feasibility study The Neuroradiology Journal ·Nicolin Hainc, Manoj Mannil, Vania Anagnostakou, Hatem Alkadhi, Christian Blüthgen, Lorenz Wacht, Andrea Bink, Shakir Husain, Zsolt Kulcsár, Sebastian Winklhofer	2020	23

About Manoj Mannil

Manoj Mannil is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics, Biomedical Engineering, Surgery and Neurology, having authored 69 papers that have together received 1.4k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (25 papers), Glioma Diagnosis and Treatment (18 papers), Cardiac Imaging and Diagnostics (12 papers), Advanced MRI Techniques and Applications (10 papers), Advanced X-ray and CT Imaging (8 papers), Medical Imaging Techniques and Applications (8 papers), Meningioma and schwannoma management (7 papers) and MRI in cancer diagnosis (7 papers). The work is most often cited by research in Health Informatics (96 citations), Radiology, Nuclear Medicine and Imaging (947 citations), Biomedical Engineering (605 citations), Genetics (112 citations) and Orthopedics and Sports Medicine (75 citations). Manoj Mannil has collaborated with scholars based in Switzerland, Germany and Netherlands. Frequent co-authors include Hatem Alkadhi, Robert Manka, Jochen von Spiczak, David Maintz, Bettina Baeßler, Roman Guggenberger, Sabrina Oebel, Bernhard Schmidt, Thomas Flohr and André Henning. Their work appears in journals such as Scientific Reports, Cancers, European Journal of Radiology, Investigative Radiology and European Radiology.

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