Dr Ashnil Kumar

PhD Sydney
Research Fellow in Biomedical Visual Image Analytics for Multi-disciplinary Retrieval
School of Computer Science

J12 - The School of Information Technologies
The University of Sydney

Telephone +61 2 9036 9805

Website School of Computer Science

Institute of Biomedical Engineering and Technology

Biographical details

Dr Ashnil Kumar received his PhD from the University of Sydney in 2013. He is currently a postdoctoral research fellow in the School of Computer Science conducting research into medical image analysis algorithms and their application within clinical workflows. He works closely with clinicians from a number of hospitals in Sydney, including the Royal Prince Alfred Hospital, Westmead Hospital and Nepean Hospital.

Since 2015, Dr Kumar has also been the Research Support and Development Officer for the Institute of Biomedical Engineering and Technology.

Research interests

In modern medicine, a vast amount of digital imaging information is routinely generated in all aspects of patient care. For Dr Ashnil Kumar, this represents an opportunity to view medicine from a different perspective - as a big data problem. His research seeks to develop and apply computing-based solutions that will enable us to look at collections of medical imaging information and find patterns that might indicate particular diagnoses or suggest particular treatments.

"My research involves looking at how computer algorithms can be used to analyse and understand medical imaging data; these algorithms can then be used to provide decision-making support to doctors. Specifically, I aim to derive algorithms that can see things that the human eye cannot easily notice, or algorithms that can discover patterns that may be too complex for humans to easily understand.

"Ultimately, the benefits of my research in enhancing the data-driven dimensions of medicine will flow back to the other dimensions - the biology, the chemistry and, most importantly, the people (both patients and clinicians).

"The ultimate application of my research will be the development of computerised decision-support systems that use image analysis algorithms to provide additional information to doctors, such as highlighting suspicious areas or comparing current images to previous scans to track progress of disease or effectiveness of treatment. This will increase the efficiency and effectiveness of patient care.

"I've been working in this field - and at the University of Sydney - since 2007. Being here means being surrounded by and collaborating with some of the best researchers in Australia and the world, both within and outside my faculty. Being able to also work with staff from the University's clinical schools at RPA, Nepean and Westmead ensures that my research remains clinically relevant."

Teaching and supervision

INFO5306 - Enterprise Healthcare Information Systems

Awards and honours

  • Award of Excellence, Institute of Biomedical Engineering and Technology (2016)
  • Faculty Teaching Commendation - COMP5206 (2015)
  • MICCAI CMMI Best Paper Award (2015)
  • ImageCLEF Liver CT Annotation Challenge - First Place (2014)
  • IEEE Journal of Biomedical and Health Informatics Best Reviewers (2014)
  • Faculty Teaching Commendation - COMP5214 (2014)
  • EuroPACS - Best Poster Award (2012)

Themes

Biomedical engineering and technology

Selected grants

2018

  • Australian Research Council Training Centre for Innovative BioEngineering; Zreiqat H, Suaning G, Feng D, Berndt C, Li Q, Dunstan C, Kim J, McEwan A, Whitchurch C, Chandrawati R, Roohaniesfahani S, Li J, Kumar A, Fulham M, Muderis M, Rutkove S, Smith W, Kappelt G, Sadeghpour A, Nisbet D, Williams R; Australian Research Council (ARC)/Industrial Transformation Training Centres (ITTC).

Selected publications

Download citations: PDF RTF Endnote

Book Chapters

  • Kim, J., Kumar, A., Cai, W., Feng, D. (2011). Multi-modal Content Based Image Retrieval in Healthcare: Current Applications and Future Challenges. In Joseph Tan (Eds.), New Technologies for Advancing Healthcare and Clinical Practices, (pp. 44-59). Pennsylvania, USA: Medical Information Science Reference.

Journals

  • Bi, L., Kim, J., Ahn, E., Kumar, A., Feng, D., Fulham, M. (2019). Step-wise integration of deep class-specific learning for dermoscopic image segmentation. Pattern Recognition, 85, 78-89. [More Information]
  • Jung, Y., Kim, J., Kumar, A., Feng, D., Fulham, M. (2018). Feature of Interest-Based Direct Volume Rendering Using Contextual Saliency-Driven Ray Profile Analysis. Computer Graphics Forum, 37(6), 5-19. [More Information]
  • Kumar, A., Kim, J., Lyndon, D., Fulham, M., Feng, D. (2017). An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification. IEEE Journal of Biomedical and Health Informatics, 21(1), 31-40. [More Information]
  • Bi, L., Kim, J., Kumar, A., Wen, L., Feng, D., Fulham, M. (2017). Automatic detection and classification of regions of FDG uptake in whole-body PET-CT lymphoma studies. Computerized Medical Imaging and Graphics, 60, 3-10. [More Information]
  • Sridar, P., Kumar, A., Li, C., Woo, J., Quinton, A., Benzie, R., Peek, M., Feng, D., Kumar, R., Nanan, R., Kim, J. (2017). Automatic Measurement of Thalamic Diameter in 2D Fetal Ultrasound Brain Images using Shape Prior Constrained Regularized Level Sets. IEEE Journal of Biomedical and Health Informatics, 21(4), 1069-1078. [More Information]
  • Bi, L., Kim, J., Ahn, E., Kumar, A., Fulham, M., Feng, D. (2017). Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks. IEEE Transactions on Biomedical Engineering, 64(9), 2065-2074. [More Information]
  • Itoh, T., Kumar, A., Klein, K., Kim, J. (2017). High-dimensional data visualization by interactive construction of low-dimensional parallel coordinate plots. Journal of Visual Languages and Computing, 43, 1-13. [More Information]
  • Ahn, E., Kim, J., Bi, L., Kumar, A., Li, C., Fulham, M., Feng, D. (2017). Saliency-Based Lesion Segmentation via Background Detection in Dermoscopic Images. IEEE Journal of Biomedical and Health Informatics, 21(6), 1685-1693. [More Information]
  • Bi, L., Kim, J., Kumar, A., Fulham, M., Feng, D. (2017). Stacked fully convolutional networks with multi-channel learning: application to medical image segmentation. The Visual Computer, 33(6-Aug), 1061-1071. [More Information]
  • Kumar, A., Dyer, S., Kim, J., Li, C., Leong, P., Fulham, M., Feng, D. (2016). Adapting content-based image retrieval techniques for the semantic annotation of medical images. Computerized Medical Imaging and Graphics, 49, 37-45. [More Information]
  • Jung, Y., Kim, J., Kumar, A., Feng, D., Fulham, M. (2016). Efficient visibility-driven medical image visualisation via adaptive binned visibility histogram. Computerized Medical Imaging and Graphics, 51, 40-49. [More Information]
  • Kumar, A., Nette, F., Klein, K., Fulham, M., Kim, J. (2015). A Visual Analytics Approach Using the Exploration of Multidimensional Feature Spaces for Content-Based Medical Image Retrieval. IEEE Journal of Biomedical and Health Informatics, 19(5), 1734-1746. [More Information]
  • Kumar, A., Kim, J., Wen, L., Fulham, M., Feng, D. (2014). A graph-based approach for the retrieval of multi-modality medical images. Medical Image Analysis, 18(2), 330-342. [More Information]
  • Constantinescu, L., Kim, J., Kumar, A., Haraguchi, D., Wen, L., Feng, D. (2013). A patient-centric distribution architecture for medical image sharing. Health Information Science and Systems, 1(3), 1-14. [More Information]
  • Kumar, A., Kim, J., Cai, W., Fulham, M., Feng, D. (2013). Content-Based Medical Image Retrieval: A Survey of Applications to Multidimensional and Multimodality Data. Journal of Digital Imaging, 26(6), 1025-1039. [More Information]
  • Kumar, A., Kim, J., Bi, L., Fulham, M., Feng, D. (2013). Designing user interfaces to enhance human interpretation of medical content-based image retrieval: application to PET-CT images. International Journal of Computer Assisted Radiology and Surgery, 8(6), 1003-1014. [More Information]
  • Kumar, A., Kim, J., Bi, L., Feng, D. (2012). An image retrieval interface for volumetric multi-modal medical data: application to PET-CT content-based image retrieva. International Journal of Computer Assisted Radiology and Surgery, 7(1 (Suppl)), 475-477. [More Information]
  • Kumar, A., Kim, J., Haraguchi, D., Wen, L., Eberl, S., Fulham, M., Feng, D. (2011). A query and visualisation interface for a PET-CT image retrieval system. International Journal of Computer Assisted Radiology and Surgery, 6(Supplement 1), 68-69.
  • Kim, J., Kumar, A., Wen, L., Eberl, S., Fulham, M., Feng, D. (2011). Visual Tracking of Treatment Response in PET-CT Image Sequences. International Journal of Computer Assisted Radiology and Surgery, , 17-18.

Conferences

  • Chi, Y., Bi, L., Kim, J., Feng, D., Kumar, A. (2018). Controlled Synthesis of Dermoscopic Images via a New Color Labeled Generative Style Transfer Network to Enhance Melanoma Segmentation. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018, Piscataway: IEEE Computer Society. [More Information]
  • Xia, T., Kumar, A., Feng, D., Kim, J. (2018). Patch-Level Tumor Classification in Digital Histopathology Images with Domain Adapted Deep Learning. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018, Piscataway: IEEE Computer Society. [More Information]
  • Lyndon, D., Kumar, A., Kim, J. (2017). Neural captioning for the ImageCLEF 2017 medical image challenges. 18th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2017, Aachen, Germany: CEUR-WS.
  • Bi, L., Kim, J., Kumar, A., Feng, D., Fulham, M. (2017). Synthesis of positron emission tomography (PET) images via multi-channel generative adversarial networks (GANs). Fifth International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, Cham: Springer International Publishing. [More Information]
  • Bi, L., Kim, J., Kumar, A., Feng, D., Fulham, M. (2016). Adaptive Supervoxel Patch-based Region Classification in Whole-Body PET-CT. 18th International Conference on Medical Image Computing and Computer Assisted Interventions MICCAI15 and Computational Methods for Molecular Imaging (CMMI 2015), Munich, Germany: Springer Lecture Notes in Computer Science.
  • Jung, Y., Kim, J., Kumar, A., Fulham, M., Feng, D. (2016). An intuitive sketch-based transfer function design via contextual and regional labelling. 33rd Computer Graphics International Conference (CGI 2016), New York: Association for Computing Machinery (ACM). [More Information]
  • Kumar, A., Sridar, P., Quinton, A., Kumar, R., Feng, D., Nanan, R., Kim, J. (2016). Plane Identification in Fetal Ultrasound Images Using Saliency Maps and Convolutional Neural Networks. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kumar, A., Lyndon, D., Kim, J., Feng, D. (2016). Subfigure and Multi-Label Classification using a Fine-Tuned Convolutional Neural Network. CLEF 2016 Conference and Labs of the Evaluation Forum, Evora: CEUR-WS.
  • Phan, H., Kumar, A., Kim, J., Feng, D. (2016). Transfer Learning of a Convolutional Neural Network for HEp-2 Cell Image Classification. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Ahn, E., Kumar, A., Kim, J., Li, C., Feng, D., Fulham, M. (2016). X-Ray Image Classification using Domain Transferred Convolutional Neural Networks and Local Sparse Spatial Pyramid. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Sridar, P., Li, C., Kumar, A., Quinton, A., Benzie, R., Peek, M., Kumar, R., Kim, J., Nanan, R. (2015). Automatic measurement of thalamic diameter in 2D fetal US brain images using shape prior constrained regularized level sets. 2nd Annual Congress of the DOHaD Society of Australia and New Zealand (DOHaD 2015 Conference), Melbourne: DOHAD Society of Australia & New Zealand.
  • Lyndon, D., Kumar, A., Kim, J., Leong, P., Feng, D. (2015). Convolutional Neural Networks for Medical Clustering. CLEF 2015 Conference and Labs of the Evaluation Forum, Toulouse: CEUR-WS.
  • Lyndon, D., Kumar, A., Kim, J., Leong, P., Feng, D. (2015). Convolutional Neural Networks for Subfigure Classification. CLEF 2015 Conference and Labs of the Evaluation Forum, Toulouse: CEUR-WS.
  • Kumar, A., Dyer, S., Li, C., Leong, P., Kim, J. (2014). Automatic annotation of liver CT images: the submission of the BMET group to ImageCLEFmed. CLEF 2014 Conference and Labs of the Evaluation Forum, United Kingdom: CEUR-WS.
  • Kumar, A., Kim, J., Fulham, M., Feng, D. (2014). Creating graph abstractions for the interpretation of combined functional and anatomical medical images. The First International Workshop on Graph Visualization in Practice, Melbourne: CEUR-WS.
  • Kumar, A., Kim, J., Fulham, M., Feng, D. (2014). Efficient PET-CT image retrieval using graphs embedded into a vector space. 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), Chicago: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • De Ridder, M., Constantinescu, L., Bi, L., Jung, Y., Kumar, A., Kim, J., Feng, D., Fulham, M. (2013). A web-based medical multimedia visualisation interface for personal health records. 26th IEEE International Symposium on Computer-Based Medical Systems (CBMS), Porto: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Bi, L., Kim, J., Wen, L., Kumar, A., Fulham, M., Feng, D. (2013). Cellular automata and anisotropic diffusion filter based interactive tumor segmentation for positron emission tomography. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kumar, A., Kim, J., Feng, D., Fulham, M. (2013). Graph-based retrieval of PET-CT images using vector space embedding. 26th IEEE International Symposium on Computer-Based Medical Systems (CBMS), Porto: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kumar, A., Kim, J., Wen, L., Feng, D. (2012). A Graph-Based Approach to the Retrieval of Volumetric PET-CT Lung Images. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kumar, A., Kim, J., Feng, D., Fulham, M. (2012). Graph-Based Retrieval of Multi-Modality Medical Images: A Comparison of Representations Using Simulated Images. The 25th International Symposium on Computer-Based Medical Systems (CBMS 2012), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Haraguchi, D., Kim, J., Kumar, A., Constantinescu, L., Wen, L., Feng, D. (2011). A Web-based Image Viewer for Multiple PET-CT Follow-Up Studies. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kumar, A., Kim, J., Cai, W., Eberl, S., Feng, D. (2008). A Graph-Based Approach to the Retrieval of Dual-Modality Biomedical Images Using Spatial Relationships. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 08), USA: Institute of Electrical and Electronics Engineers (IEEE).
  • Kim, J., Kumar, A., Eberl, S., Fulham, M., Feng, D. (2008). Interactive Point-of-Interest Volume Rendering Visualization of PET-CT Data. 2008 IEEE Nuclear Science Symposium, Medical Imaging Conference and 16th International Workshop on Room-temperature Semiconductor X- and Gamma-Ray Detectors (RTSD), CD-Rom: Institute of Electrical and Electronics Engineers (IEEE).

2019

  • Bi, L., Kim, J., Ahn, E., Kumar, A., Feng, D., Fulham, M. (2019). Step-wise integration of deep class-specific learning for dermoscopic image segmentation. Pattern Recognition, 85, 78-89. [More Information]

2018

  • Chi, Y., Bi, L., Kim, J., Feng, D., Kumar, A. (2018). Controlled Synthesis of Dermoscopic Images via a New Color Labeled Generative Style Transfer Network to Enhance Melanoma Segmentation. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018, Piscataway: IEEE Computer Society. [More Information]
  • Jung, Y., Kim, J., Kumar, A., Feng, D., Fulham, M. (2018). Feature of Interest-Based Direct Volume Rendering Using Contextual Saliency-Driven Ray Profile Analysis. Computer Graphics Forum, 37(6), 5-19. [More Information]
  • Xia, T., Kumar, A., Feng, D., Kim, J. (2018). Patch-Level Tumor Classification in Digital Histopathology Images with Domain Adapted Deep Learning. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018, Piscataway: IEEE Computer Society. [More Information]

2017

  • Kumar, A., Kim, J., Lyndon, D., Fulham, M., Feng, D. (2017). An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification. IEEE Journal of Biomedical and Health Informatics, 21(1), 31-40. [More Information]
  • Bi, L., Kim, J., Kumar, A., Wen, L., Feng, D., Fulham, M. (2017). Automatic detection and classification of regions of FDG uptake in whole-body PET-CT lymphoma studies. Computerized Medical Imaging and Graphics, 60, 3-10. [More Information]
  • Sridar, P., Kumar, A., Li, C., Woo, J., Quinton, A., Benzie, R., Peek, M., Feng, D., Kumar, R., Nanan, R., Kim, J. (2017). Automatic Measurement of Thalamic Diameter in 2D Fetal Ultrasound Brain Images using Shape Prior Constrained Regularized Level Sets. IEEE Journal of Biomedical and Health Informatics, 21(4), 1069-1078. [More Information]
  • Bi, L., Kim, J., Ahn, E., Kumar, A., Fulham, M., Feng, D. (2017). Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks. IEEE Transactions on Biomedical Engineering, 64(9), 2065-2074. [More Information]
  • Itoh, T., Kumar, A., Klein, K., Kim, J. (2017). High-dimensional data visualization by interactive construction of low-dimensional parallel coordinate plots. Journal of Visual Languages and Computing, 43, 1-13. [More Information]
  • Lyndon, D., Kumar, A., Kim, J. (2017). Neural captioning for the ImageCLEF 2017 medical image challenges. 18th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2017, Aachen, Germany: CEUR-WS.
  • Ahn, E., Kim, J., Bi, L., Kumar, A., Li, C., Fulham, M., Feng, D. (2017). Saliency-Based Lesion Segmentation via Background Detection in Dermoscopic Images. IEEE Journal of Biomedical and Health Informatics, 21(6), 1685-1693. [More Information]
  • Bi, L., Kim, J., Kumar, A., Fulham, M., Feng, D. (2017). Stacked fully convolutional networks with multi-channel learning: application to medical image segmentation. The Visual Computer, 33(6-Aug), 1061-1071. [More Information]
  • Bi, L., Kim, J., Kumar, A., Feng, D., Fulham, M. (2017). Synthesis of positron emission tomography (PET) images via multi-channel generative adversarial networks (GANs). Fifth International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, Cham: Springer International Publishing. [More Information]

2016

  • Kumar, A., Dyer, S., Kim, J., Li, C., Leong, P., Fulham, M., Feng, D. (2016). Adapting content-based image retrieval techniques for the semantic annotation of medical images. Computerized Medical Imaging and Graphics, 49, 37-45. [More Information]
  • Bi, L., Kim, J., Kumar, A., Feng, D., Fulham, M. (2016). Adaptive Supervoxel Patch-based Region Classification in Whole-Body PET-CT. 18th International Conference on Medical Image Computing and Computer Assisted Interventions MICCAI15 and Computational Methods for Molecular Imaging (CMMI 2015), Munich, Germany: Springer Lecture Notes in Computer Science.
  • Jung, Y., Kim, J., Kumar, A., Fulham, M., Feng, D. (2016). An intuitive sketch-based transfer function design via contextual and regional labelling. 33rd Computer Graphics International Conference (CGI 2016), New York: Association for Computing Machinery (ACM). [More Information]
  • Jung, Y., Kim, J., Kumar, A., Feng, D., Fulham, M. (2016). Efficient visibility-driven medical image visualisation via adaptive binned visibility histogram. Computerized Medical Imaging and Graphics, 51, 40-49. [More Information]
  • Kumar, A., Sridar, P., Quinton, A., Kumar, R., Feng, D., Nanan, R., Kim, J. (2016). Plane Identification in Fetal Ultrasound Images Using Saliency Maps and Convolutional Neural Networks. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kumar, A., Lyndon, D., Kim, J., Feng, D. (2016). Subfigure and Multi-Label Classification using a Fine-Tuned Convolutional Neural Network. CLEF 2016 Conference and Labs of the Evaluation Forum, Evora: CEUR-WS.
  • Phan, H., Kumar, A., Kim, J., Feng, D. (2016). Transfer Learning of a Convolutional Neural Network for HEp-2 Cell Image Classification. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Ahn, E., Kumar, A., Kim, J., Li, C., Feng, D., Fulham, M. (2016). X-Ray Image Classification using Domain Transferred Convolutional Neural Networks and Local Sparse Spatial Pyramid. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2015

  • Kumar, A., Nette, F., Klein, K., Fulham, M., Kim, J. (2015). A Visual Analytics Approach Using the Exploration of Multidimensional Feature Spaces for Content-Based Medical Image Retrieval. IEEE Journal of Biomedical and Health Informatics, 19(5), 1734-1746. [More Information]
  • Sridar, P., Li, C., Kumar, A., Quinton, A., Benzie, R., Peek, M., Kumar, R., Kim, J., Nanan, R. (2015). Automatic measurement of thalamic diameter in 2D fetal US brain images using shape prior constrained regularized level sets. 2nd Annual Congress of the DOHaD Society of Australia and New Zealand (DOHaD 2015 Conference), Melbourne: DOHAD Society of Australia & New Zealand.
  • Lyndon, D., Kumar, A., Kim, J., Leong, P., Feng, D. (2015). Convolutional Neural Networks for Medical Clustering. CLEF 2015 Conference and Labs of the Evaluation Forum, Toulouse: CEUR-WS.
  • Lyndon, D., Kumar, A., Kim, J., Leong, P., Feng, D. (2015). Convolutional Neural Networks for Subfigure Classification. CLEF 2015 Conference and Labs of the Evaluation Forum, Toulouse: CEUR-WS.

2014

  • Kumar, A., Kim, J., Wen, L., Fulham, M., Feng, D. (2014). A graph-based approach for the retrieval of multi-modality medical images. Medical Image Analysis, 18(2), 330-342. [More Information]
  • Kumar, A., Dyer, S., Li, C., Leong, P., Kim, J. (2014). Automatic annotation of liver CT images: the submission of the BMET group to ImageCLEFmed. CLEF 2014 Conference and Labs of the Evaluation Forum, United Kingdom: CEUR-WS.
  • Kumar, A., Kim, J., Fulham, M., Feng, D. (2014). Creating graph abstractions for the interpretation of combined functional and anatomical medical images. The First International Workshop on Graph Visualization in Practice, Melbourne: CEUR-WS.
  • Kumar, A., Kim, J., Fulham, M., Feng, D. (2014). Efficient PET-CT image retrieval using graphs embedded into a vector space. 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), Chicago: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2013

  • Constantinescu, L., Kim, J., Kumar, A., Haraguchi, D., Wen, L., Feng, D. (2013). A patient-centric distribution architecture for medical image sharing. Health Information Science and Systems, 1(3), 1-14. [More Information]
  • De Ridder, M., Constantinescu, L., Bi, L., Jung, Y., Kumar, A., Kim, J., Feng, D., Fulham, M. (2013). A web-based medical multimedia visualisation interface for personal health records. 26th IEEE International Symposium on Computer-Based Medical Systems (CBMS), Porto: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Bi, L., Kim, J., Wen, L., Kumar, A., Fulham, M., Feng, D. (2013). Cellular automata and anisotropic diffusion filter based interactive tumor segmentation for positron emission tomography. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kumar, A., Kim, J., Cai, W., Fulham, M., Feng, D. (2013). Content-Based Medical Image Retrieval: A Survey of Applications to Multidimensional and Multimodality Data. Journal of Digital Imaging, 26(6), 1025-1039. [More Information]
  • Kumar, A., Kim, J., Bi, L., Fulham, M., Feng, D. (2013). Designing user interfaces to enhance human interpretation of medical content-based image retrieval: application to PET-CT images. International Journal of Computer Assisted Radiology and Surgery, 8(6), 1003-1014. [More Information]
  • Kumar, A., Kim, J., Feng, D., Fulham, M. (2013). Graph-based retrieval of PET-CT images using vector space embedding. 26th IEEE International Symposium on Computer-Based Medical Systems (CBMS), Porto: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2012

  • Kumar, A., Kim, J., Wen, L., Feng, D. (2012). A Graph-Based Approach to the Retrieval of Volumetric PET-CT Lung Images. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kumar, A., Kim, J., Bi, L., Feng, D. (2012). An image retrieval interface for volumetric multi-modal medical data: application to PET-CT content-based image retrieva. International Journal of Computer Assisted Radiology and Surgery, 7(1 (Suppl)), 475-477. [More Information]
  • Kumar, A., Kim, J., Feng, D., Fulham, M. (2012). Graph-Based Retrieval of Multi-Modality Medical Images: A Comparison of Representations Using Simulated Images. The 25th International Symposium on Computer-Based Medical Systems (CBMS 2012), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2011

  • Kumar, A., Kim, J., Haraguchi, D., Wen, L., Eberl, S., Fulham, M., Feng, D. (2011). A query and visualisation interface for a PET-CT image retrieval system. International Journal of Computer Assisted Radiology and Surgery, 6(Supplement 1), 68-69.
  • Haraguchi, D., Kim, J., Kumar, A., Constantinescu, L., Wen, L., Feng, D. (2011). A Web-based Image Viewer for Multiple PET-CT Follow-Up Studies. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kim, J., Kumar, A., Cai, W., Feng, D. (2011). Multi-modal Content Based Image Retrieval in Healthcare: Current Applications and Future Challenges. In Joseph Tan (Eds.), New Technologies for Advancing Healthcare and Clinical Practices, (pp. 44-59). Pennsylvania, USA: Medical Information Science Reference.
  • Kim, J., Kumar, A., Wen, L., Eberl, S., Fulham, M., Feng, D. (2011). Visual Tracking of Treatment Response in PET-CT Image Sequences. International Journal of Computer Assisted Radiology and Surgery, , 17-18.

2008

  • Kumar, A., Kim, J., Cai, W., Eberl, S., Feng, D. (2008). A Graph-Based Approach to the Retrieval of Dual-Modality Biomedical Images Using Spatial Relationships. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 08), USA: Institute of Electrical and Electronics Engineers (IEEE).
  • Kim, J., Kumar, A., Eberl, S., Fulham, M., Feng, D. (2008). Interactive Point-of-Interest Volume Rendering Visualization of PET-CT Data. 2008 IEEE Nuclear Science Symposium, Medical Imaging Conference and 16th International Workshop on Room-temperature Semiconductor X- and Gamma-Ray Detectors (RTSD), CD-Rom: Institute of Electrical and Electronics Engineers (IEEE).

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