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Qiang Zhang

Postdoctoral Researcher

Machine Learning in Medical Imaging

My research has been focused on bridging between machine learning (especially deep learning) techniques and cardiovascular research, by translating cardiovascular problems into computing models, and automating cardiovascular data processing with machine learning algorithms. The goal is to reduce the workload of clinicians, to help understand the pattern of diseases, and to improve the diagnostic accuracy.

  1. Qiang Zhang, Abhir Bhalerao, and Charles Hutchinson: "Deformable Appearance Pyramids for Anatomy Representation, Landmark Detection and Pathology Classification", MICCAI Special issue, IJCARS, 2017.
  2. Qiang Zhang, Abhir Bhalerao, Edward Dickenson, and Charles Hutchinson. "Active appearance pyramids for object parametrisation and fitting." Medical Image Analysis (2016), (PDF Document)
  3. Qiang Zhang, Abhir Bhalerao, and Charles Hutchinson, "Weakly supervised evidence pinpointing and description", Biennial International conference on Information Processing in Medical Imaging (IPMI 2017), North Carolina, USA, Jun 2017.
  4. Qiang Zhang, Abhir Bhalerao, Caron Parsons, Emma Helm, and Charles Hutchinson, "Wavelet Appearance Pyramids for Landmark Detection and Pathology Classification: Application to Lumbar Spinal Stenosis. " Medical Image Computing and Computer Assisted Intervention (MICCAI 2016), Athens, Oct 2016, (PDF Document), appendix (PDF Document)url:
  5. Qiang Zhang, Abhir Bhalerao, "Loglet SIFT for Part Description in Deformable Part Models: Application to Face Alignment", British Machine Vision Conference 2016, York, Sep 2016, (PDF Document)
  6. Qiang Zhang, Abhir Bhalerao, Emma Helm, and Charles Hutchinson. "Active shape model unleashed with multi-scale local appearance." IEEE International Conference on Image Processing 2015, Quebec City, Oct 2015, slides (Powerpoint Presentation) , paper(PDF Document).
  7. Caron Parsons, Charles Hutchinson, Emma Helm, Alexander Clarke, Asfand Baig Mirza, Qiang Zhang, and Abhir Bhalerao. Development of an Automated Shape and Textural Software Model of the Paediatric Knee for Estimation of Skeletal Age. International Society for Magnetic Resonance in Medicine 2016), The 24th Annual Meeting and Exhibition, Singapore, 7-13 May 2016.