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Fast and high-resolution medical imaging

Guest Editors:
Kanika Bhalla: Washington University, St. Louis, USA 
Satya VVN Kothapalli: Washington University, St. Louis, USA 
Prabhishek Singh: Bennett University, India                  


BMC Medical Imaging called for submissions to our Collection on Fast and high-resolution medical imaging. This collection welcomed articles presenting advances in resolution for imaging technologies of clinical relevance for any medical area including neuroscience, cardiology, oncology and surgery. This includes but is not limited to novel developments of techniques, materials, and protocols able to achieve a higher resolution, with particular attention to their diagnostic value. Comparative studies were also warmly welcomed. 

Meet the Guest Editors

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Kanika Bhalla: Washington University, St. Louis, USA

Dr Kanika Bhalla received her Ph.D. degree in electrical engineering and computer science from the National Taipei University of Technology, Taipei, Taiwan. She is currently a postdoctoral research associate at the Washington University School of Medicine in St. Louis, Missouri, in the United States. She worked as a lecturer in the computer science department of Chitkara University in India. Her current research interests include machine learning, deep learning modelling, fuzzy systems design and modelling, medical image processing, computer vision, pattern recognition, segmentation, defects detection, and multimodality image fusion.

Satya VVN Kothapalli: Washington University, St. Louis, USA                                                                                                          
Dr Satya VVN Kothapalli received a Ph.D. in the Department of Medical Imaging at the School of Technology and Health, STH, Royal Institute of Technology-KTH in Stockholm, Sweden. He is working as a Staff Scientist in the Department of Radiology at Washington University School of Medicine, Saint Louis. He is currently involving in fields of quantitative magnetic resonance imaging for assessing the neuronal damage in neurodegenerative diseases in the brain. His research interests include developing novel quantitative MRI methods, developing MR based imaging biomarkers for early Alzheimer’s diseases, MR guided focused ultrasound, and multimodal contrast agents. 

Prabhishek Singh: Bennett University, India                                                                                                          
Dr Prabhishek Singh (Senior IEEE Member) is working as an Assistant Professor in the School of Computer Science Engineering and Technology, Bennett University (The Times Group), Greater Noida, India. He has published 120+ research papers in SCI/SCIE/Scopus, ESCI journals, and conferences. His research interest includes Satellite and Medical Image Processing and Computer Vision, Deep Learning, and Machine Learning. He serves as a Senior Editor, Associate Editor, Academic Editor, Review Editor, Leading Guest Editor, Reviewer, and Editorial Committee Chair of many SCI/SCIE/Scopus and ESCI journals, and other prestigious conferences.

About the collection

BMC Medical Imaging is calling for submissions to our Collection on Fast and high-resolution medical imaging. New advances in the clinical use of imaging technologies are correlated with enhanced resolution, either achieved through new contrast media or improved processing tools. This collection welcomes articles presenting advances in resolution for imaging technologies of clinical relevance for any medical area including neuroscience, cardiology, oncology and surgery. This includes but is not limited to novel developments of techniques, materials, and protocols able to achieve a higher resolution, with particular attention to their diagnostic value. Comparative studies are also warmly welcomed. 


Image credit: Maksym Povozniuk/stock.adobe.com

  1. Preoperative discrimination between non-muscle-invasive bladder cancer (NMIBC) and the muscle invasive bladder cancer (MIBC) is a determinant of management. The purpose of this research is to employ radiomics ...

    Authors: Shuo Li, Zhichang Fan, Junting Guo, Ding Li, Zeke Chen, Xiaoyue Zhang, Yongfang Wang, Yan Li, Guoqiang Yang and Xiaochun Wang
    Citation: BMC Medical Imaging 2024 24:148
    Content type: Research Published on:

  2. This study developed and validated a nomogram utilizing clinical and multi-slice spiral computed tomography (MSCT) features for the preoperative prediction of Ki-67 expression in stage IA lung adenocarcinoma. ...

    Authors: Zhengteng Li, Hongmei Liu, Min Wang, Xiankai Wang, Dongmei Pan, Aidong Ma and Yang Chen
    Citation: BMC Medical Imaging 2024 24:143
    Content type: Research Published on:

  3. The presence of infarction in patients with unrecognized myocardial infarction (UMI) is a critical feature in predicting adverse cardiac events. This study aimed to compare the detection rate of UMI using conv...

    Authors: Xuefang Lu, Weiyin Vivian Liu, Yuchen Yan, Wenbing Yang, Changsheng Liu, Wei Gong, Guangnan Quan, Jiawei Jiang, Lei Yuan and Yunfei Zha
    Citation: BMC Medical Imaging 2024 24:127
    Content type: Research Published on:

  4. Brain tumor diagnosis using MRI scans poses significant challenges due to the complex nature of tumor appearances and variations. Traditional methods often require extensive manual intervention and are prone t...

    Authors: Asma Alshuhail, Arastu Thakur, R Chandramma, T R Mahesh, Ahlam Almusharraf, V Vinoth Kumar and Surbhi Bhatia Khan
    Citation: BMC Medical Imaging 2024 24:118
    Content type: Research Published on:

  5. Brain tumor classification using MRI images is a crucial yet challenging task in medical imaging. Accurate diagnosis is vital for effective treatment planning but is often hindered by the complex nature of tum...

    Authors: Eid Albalawi, Mahesh T.R., Arastu Thakur, V. Vinoth Kumar, Muskan Gupta, Surbhi Bhatia Khan and Ahlam Almusharraf
    Citation: BMC Medical Imaging 2024 24:110
    Content type: Research Published on:

  6. Categorizing Artificial Intelligence of Medical Things (AIoMT) devices within the realm of standard Internet of Things (IoT) and Internet of Medical Things (IoMT) devices, particularly at the server and comput...

    Authors: Syed Thouheed Ahmed, T. R. Mahesh, E. Srividhya, V. Vinoth Kumar, Surbhi Bhatia Khan, Abdullah Albuali and Ahlam Almusharraf
    Citation: BMC Medical Imaging 2024 24:105
    Content type: Research Published on:

  7. Precision and intelligence in evaluating the complexities of middle ear structures are required to diagnose auriculotemporal and ossicle-related diseases within otolaryngology. Due to the complexity of the ana...

    Authors: Qinfang Cai, Peishan Zhang, Fengmei Xie, Zedong Zhang and Bo Tu
    Citation: BMC Medical Imaging 2024 24:102
    Content type: Research Published on:

  8. Medical imaging AI systems and big data analytics have attracted much attention from researchers of industry and academia. The application of medical imaging AI systems and big data analytics play an important...

    Authors: Rui Sun, Zhengyin Zhang, Yajun Liu, Xiaohang Niu and Jie Yuan
    Citation: BMC Medical Imaging 2024 24:86
    Content type: Research Published on:

  9. The research focuses on the segmentation and classification of leukocytes, a crucial task in medical image analysis for diagnosing various diseases. The leukocyte dataset comprises four classes of images such ...

    Authors: Vatsala Anand, Sheifali Gupta, Deepika Koundal, Wael Y. Alghamdi and Bayan M. Alsharbi
    Citation: BMC Medical Imaging 2024 24:83
    Content type: Research Published on:

  10. The paper aimed to improve the accuracy limitations of traditional two-dimensional ultrasound and surgical procedures in the diagnosis and management of congenital heart disease (chd), and to improve the diagn...

    Authors: Yong Jiang
    Citation: BMC Medical Imaging 2024 24:61
    Content type: Research Published on:

  11. MULTIPLEX is a single-scan three-dimensional multi-parametric MRI technique that provides 1 mm isotropic T1-, T2*-, proton density- and susceptibility-weighted images and the corresponding quantitative maps. T...

    Authors: Min Duan, Rongrong Pan, Qing Gao, Xinying Wu, Hai Lin, Jianmin Yuan, Yamei Zhang, Lindong Liu, Youyong Tian and Tong Fu
    Citation: BMC Medical Imaging 2024 24:58
    Content type: Research Published on:

  12. Lung diseases, both infectious and non-infectious, are the most prevalent cause of mortality overall in the world. Medical research has identified pneumonia, lung cancer, and Corona Virus Disease 2019 (COVID-1...

    Authors: Sunil Kumar, Harish Kumar, Gyanendra Kumar, Shailendra Pratap Singh, Anchit Bijalwan and Manoj Diwakar
    Citation: BMC Medical Imaging 2024 24:30
    Content type: Research Published on:

  14. Brain CT can be used to evaluate pediatric patients with suspicion of cerebral pathology when anesthetic and MRI resources are scarce. This study aimed to assess if pediatric patients referred for an elective ...

    Authors: Francesca De Luca, Annika Kits, Daniel Martin Muñoz, Åsa Aspelin, Ola Kvist, Yords Österman, Sandra Diaz Ruiz, Stefan Skare and Anna Falk Delgado
    Citation: BMC Medical Imaging 2024 24:23
    Content type: Research Published on:

  15. Deep learning is a highly significant technology in clinical treatment and diagnostics nowadays. Convolutional Neural Network (CNN) is a new idea in deep learning that is being used in the area of computer vis...

    Authors: Sohamkumar Chauhan, Damoder Reddy Edla, Vijayasree Boddu, M Jayanthi Rao, Ramalingaswamy Cheruku, Soumya Ranjan Nayak, Sheshikala Martha, Kamppa Lavanya and Tsedenya Debebe Nigat
    Citation: BMC Medical Imaging 2024 24:1
    Content type: Research Published on:

  16. Medical images such as CT and X-ray have been widely used for the detection of several chest infections and lung diseases. However, these images are susceptible to different types of noise, and it is hard to r...

    Authors: Tapan Kumar Nayak, Chandra Sekhara Rao Annavarappu, Soumya Ranjan Nayak and Berihun Molla Gedefaw
    Citation: BMC Medical Imaging 2023 23:150
    Content type: Research Published on:

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Fast and high-resolution medical imaging" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.