Publications

Preprints

No current preprints.

Journal Publications

AortaSeg24 multi-class aortic segmentation

30. Imran, M., Krebs, J. R., Sivaraman, V. B., Zhang, T., Kumar, A., Ueland, W. R., Fassler, M. J., Wang, C., Huang, J., Sun, X., et al. (2026). Multi-class segmentation of aortic branches and zones in computed tomography angiography: The AortaSeg24 challenge. Medical Image Analysis, 113, 104188. https://doi.org/10.1016/j.media.2026.104188.

Comparison of Maximal Aortic Diameter Measurements

29. Cooper, M. A., Ueland, W. R., Wang, C., Fassler, M. J., Stinson, G., Krebs, J. R., Fazzone, B., Imran, M., Upchurch, G. R., & Shao, W. (2026). Comparison of maximal aortic diameter measurements by training level to an automated deep learning model. Journal of Vascular Surgery, 83(5), S50–S51. https://doi.org/10.1016/j.jvs.2025.12.262.

AI-enhanced micro-ultrasound prostate cancer detection

28. Imran, M., Brisbane, W. G., Su, L.-M., Joseph, J. P., & Shao, W. (2026). AI-enhanced micro-ultrasound improves detection of clinically significant prostate cancer at biopsy. BJUI Compass, 7(2), e70133. https://doi.org/10.1002/bco2.70133.

Fast-DDPM models for medical image generation

27. Jiang, H., Imran, M., Zhang, T., Zhou, Y., Liang, M., Gong, K., & Shao, W. (2025). Fast-DDPM: Fast denoising diffusion probabilistic models for medical image-to-image generation. IEEE Journal of Biomedical and Health Informatics, 29(10), 7326–7335. https://doi.org/10.1109/JBHI.2025.3565183.

Dual residual dense network for image denoising

26. Batool, I., & Imran, M. (2025). A dual residual dense network for image denoising. Engineering Applications of Artificial Intelligence, 147, 110275. https://doi.org/10.1016/j.engappai.2025.110275.

RetinaRegNet zero-shot approach for retinal image registration

25. Sivaraman, V. B., Imran, M., Wei, Q., Muralidharan, P., Tamplin, M. R., Grumbach, I. M., Kardon, R. H., Wang, J.-K., Zhou, Y., & Shao, W. (2025). RetinaRegNet: A zero-shot approach for retinal image registration. Computers in Biology and Medicine, 186, 109645. https://doi.org/10.1016/j.compbiomed.2024.109645.

CIS-UNet multi-class segmentation of the aorta

24. Imran, M., Krebs, J. R., Gopu, V. R. R., Fazzone, B., Sivaraman, V. B., Kumar, A., Viscardi, C., Heithaus, R. E., Shickel, B., Zhou, Y., Cooper, M. A., & Shao, W. (2024). CIS-UNet: Multi-class segmentation of the aorta in computed tomography angiography via context-aware shifted window self-attention. Computerized Medical Imaging and Graphics, 118, 102470. https://doi.org/10.1016/j.compmedimag.2024.102470.

A flexible 2.5D medical image segmentation approach

23. Kumar, A., Jiang, H., Imran, M., Valdes, C., Leon, G., Kang, D., Nataraj, P., Zhou, Y., Weiss, M. D., & Shao, W. (2024). A flexible 2.5D medical image segmentation approach with in-slice and cross-slice attention. Computers in Biology and Medicine, 182, 109173. https://doi.org/10.1016/j.compbiomed.2024.109173.

Image registration of in vivo micro-ultrasound and ex vivo histopathology

22. Imran, M., Nguyen, B., Pensa, J., Falzarano, S. M., Sisk, A. E., Liang, M., DiBianco, J. M., Su, L.-M., Zhou, Y., Joseph, J. P., et al. (2024). Image registration of in vivo micro-ultrasound and ex vivo pseudo-whole mount histopathology images of the prostate: A proof-of-concept study. Biomedical Signal Processing and Control, 96, 106657. https://doi.org/10.1016/j.bspc.2024.106657.

Volumetric analysis of acute uncomplicated type B aortic dissection

21. Krebs, J. R., Imran, M., Fazzone, B., Viscardi, C., Berwick, B., Stinson, G., Heithaus, E., Upchurch Jr, G. R., Shao, W., & Cooper, M. A. (2024). Volumetric analysis of acute uncomplicated type B aortic dissection using an automated deep learning aortic zone segmentation model. Journal of Vascular Surgery, 80(4), 1025–1034.e4. https://doi.org/10.1016/j.jvs.2024.06.001.

Transformer-based hierarchical model for non-small cell lung cancer

20. Imran, M., Haq, B., Elbasi, E., Topcu, A. E., & Shao, W. (2024). Transformer-based hierarchical model for non-small cell lung cancer detection and classification. IEEE Access, 12, 145920–145933. https://doi.org/10.1109/ACCESS.2024.3449230.

MicroSegNet: deep learning approach for prostate segmentation

19. Jiang, H., Imran, M., Muralidharan, P., Patel, A., Pensa, J., Liang, M., Benidir, T., Grajo, J. R., Joseph, J. P., Terry, R., DiBianco, J. M., Su, L.-M., Zhou, Y., Brisbane, W. G., & Shao, W. (2024). MicroSegNet: A deep learning approach for prostate segmentation on micro-ultrasound images. Computerized Medical Imaging and Graphics, 112, 102326. https://doi.org/10.1016/j.compmedimag.2024.102326.

Video Stabilization using RAFT-based Optical Flow

18. Ashar, R., Sadiq, B., Mohiuddin, H., Ashraf, S., Imran, M., & Ullah, A. (2023). Video stabilization using RAFT-based optical flow. 2023 International Conference on Robotics and Automation in Industry (ICRAI), 1–5. https://doi.org/10.1109/ICRAI57502.2023.10089609.

Multi-Exposure Image Fusion Using Edge-Aware Network

17. Aslam, G., Imran, M., Haq, B., Ullah, A., & Elbasi, E. (2022). Multi-exposure image fusion using edge-aware network. 2022 17th International Conference on Emerging Technologies (ICET), 59–63. https://doi.org/10.1109/ICET56601.2022.10004672.

Learning Deep Pyramid-based Representations for Pansharpening

16. Adeel, H., Ali, S. S., Riaz, M. M., Kirmani, S. A. M., Qureshi, M. I., & Imtiaz, J. (2022). Learning deep pyramid-based representations for pansharpening. Arabian Journal for Science and Engineering, 47(8), 10655–10666. https://doi.org/10.1007/s13369-022-06657-0.

Unified technique for entropy enhancement based diabetic retinopathy detection

15. Fatima, Imran, M., Ullah, A., Arif, M., & Noor, R. (2022). A unified technique for entropy enhancement based diabetic retinopathy detection using hybrid neural network. Computers in Biology and Medicine, 145, 105424. https://doi.org/10.1016/j.compbiomed.2022.105424.

Multimodality anatomical image fusion method

14. Sufyan, A., Imran, M., Shah, S. A., Shahwani, H., & Wadood, A. A. (2022). A novel multimodality anatomical image fusion method based on contrast and structure extraction. International Journal of Imaging Systems and Technology, 32(1), 324–342. https://doi.org/10.1002/ima.22649.

Single image dehazing technique using dual transmission maps strategy

13. Ehsan, S. M., Imran, M., Ullah, A., & Elbasi, E. (2021). A single image dehazing technique using the dual transmission maps strategy and gradient-domain guided image filtering. IEEE Access, 9, 89055–89063. https://doi.org/10.1109/ACCESS.2021.3090078.

Novel de-ghosting image fusion technique for multi-exposure multi-focus images

12. Roomi, M. S., Imran, M., Shah, S. A., Almogren, A., Ali, I., & Zuair, M. (2020). A novel de-ghosting image fusion technique for multi-exposure, multi-focus images using guided image filtering. IEEE Access, 8, 219656–219671. https://doi.org/10.1109/ACCESS.2020.3043048.

Detailed and enhanced multi-exposure image fusion using recursive filter

11. Hayat, N., & Imran, M. (2020). Detailed and enhanced multi-exposure image fusion using recursive filter. Multimedia Tools and Applications, 79(33–34), 25067–25088. https://doi.org/10.1007/s11042-020-09190-0.

Multi-exposure image fusion technique using multi-resolution blending

10. Hayat, N., & Imran, M. (2019). Multi-exposure image fusion technique using multi-resolution blending. IET Image Processing, 13(13), 2554–2561. https://doi.org/10.1049/iet-ipr.2019.0438.

Ghost-free multi exposure image fusion technique

9. Hayat, N., & Imran, M. (2019). Ghost-free multi exposure image fusion technique using dense SIFT descriptor and guided filter. Journal of Visual Communication and Image Representation, 62, 295–308. https://doi.org/10.1016/j.jvcir.2019.06.002.

Block-based secure and robust watermarking scheme for color images

8. Imran, M., Harvey, B. A., Atif, M., & Memon, A. A. (2019). A block-based secure and robust watermarking scheme for color images based on multi-resolution decomposition and de-correlation. Frontiers of Information Technology & Electronic Engineering, 20(7), 946–963. https://doi.org/10.1631/FITEE.1700667.

Blind adaptive color image watermarking scheme

7. Imran, M., & Harvey, B. A. (2017). A blind adaptive color image watermarking scheme based on principal component analysis, singular value decomposition and human visual system. Radioengineering, 26(3), 823–834. https://doi.org/10.13164/re.2017.0823.

Block based blind and secure gray image watermarking technique

6. Imran, M., & Harvey, B. A. (2017). Block based blind & secure gray image watermarking technique based on discrete wavelet transform and singular value decomposition. KSII Transactions on Internet and Information Systems, 11(2), 883–900. https://doi.org/10.3837/tiis.2017.02.014.

Novel blind color image watermarking technique based on SVD and PCA

5. Imran, M., Harvey, B. A., & Memon, A. A. (2016). A novel blind color image watermarking technique based on singular value decomposition and principal component analysis. 2016 Sixth International Conference on Innovative Computing Technology (INTECH), 519–524. https://doi.org/10.1109/INTECH.2016.7845031.

Adaptive watermarking technique based on HVS and fuzzy inference system

4. Imran, M., Ghafoor, A., & Riaz, M. M. (2013). Adaptive watermarking technique based on human visual system and fuzzy inference system. 2013 IEEE International Symposium on Circuits and Systems (ISCAS), 2816–2819. https://doi.org/10.1109/ISCAS.2013.6572464.

Robust non-blind color image watermarking scheme

3. Imran, M., Ghafoor, A., & Khokher, M. R. (2012). A robust non-blind color image watermarking scheme. 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV), 1392–1396. https://doi.org/10.1109/ICARCV.2012.6485392.

PCA-DWT-SVD based color image watermarking

2. Imran, M., & Ghafoor, A. (2012). A PCA-DWT-SVD based color image watermarking. 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 1147–1152. https://doi.org/10.1109/ICSMC.2012.6377886.

A non-blind color image watermarking scheme

1. Ghafoor, A., & Imran, M. (2012). A non-blind color image watermarking scheme resistent against geometric attacks. Radioengineering, 21(4), 1246–1251.

Conference Publications

Undergraduate Publications

Other Publications

AortaSeg24 challenge proceedings

Imran, M., Krebs, J. R., Cooper, M. A., Ma, J., Zhou, Y., & Shao, W. (Eds.). (2026). Multi-class Segmentation of the Aorta: AortaSeg 2024 Challenge, Held in Conjunction with MICCAI 2024, Virtual Event, October 24, 2024, Proceedings. Lecture Notes in Computer Science, 16399. Springer. https://doi.org/10.1007/978-3-032-14246-7.