2017

Scan-less Line Field Optical Coherence Tomography, with automatic image segmentation, as a measurement tool for automotive coatings.

Lawman S, Williams BM, Zhang J, Shen YC, Zheng YL

APPLIED SCIENCES, 2017

Volumetric image classification using homogeneous decomposition and dictionary learning: A study using retinal optical coherence tomography for detecting age-related macular degeneration

Albarrak A, Coenen F, Zheng Y

COMPUT. MED. IMAG. GRAP. 2017. 55: 113-123

Automated layer segmentation of macular OCT images via graph-based SLIC superpixels and manifold ranking approach

Gao, Z., W. Bu, et al

COMPUT. MED. IMAG. GRAP. 2017. 55: 42-53

Saliency driven vasculature segmentation with infinite perimeter active contour model

Zhao, Y, Zhao J, et al

NEUROCOMPUTING 2017

Intensity and Compactness Enabled Saliency Estimation for Leakage Detection in Diabetic and Malarial Retinopathy

Zhao, Y, Zheng Y, et al

IEEE T. MED. IMAGING. 2017. 36(1): 51-63

2016

Nondestructive analysis of automotive paints with spectral domain optical coherence tomography.

Dong, Y., S. Lawman, et al.

(2016). Applied optics 55(13): 3695-3700.

High resolution corneal and single pulse imaging with line field spectral domain optical coherence tomography.

Lawman, S., Y. Dong, et al.

(2016). Optics express 24(11): 12395-12405.

Reconstruction of 3D surface maps from anterior segment optical coherence tomography images using graph theory and genetic algorithms.

Williams, D., Y. Zheng, et al.

(2016). Biomed. Signal Process. Control 25: 91-98.

A compactness based saliency approach for leakages detection in fluorescein angiogram.

Zhao, Y., P. Su, et al.

(2016). International Journal of Machine Learning and Cybernetics: 1-9.

2015

Standardization of choroidal thickness measurements using enhanced depth imaging optical coherence tomography.

Boonarpha, N., Y. Zheng, et al.

(2015). Int. J. Ophthalmol. 8(3): 484.

A new study of blind deconvolution with implicit incorporation of nonnegativity constraints.

Chen, K., S. P. Harding, et al.

(2015). Int. J. Comput. Math. 2015.

Angiographic and in vivo confocal microscopic characterization of human corneal blood and presumed lymphatic neovascularization: a pilot study.

Romano, V., B. Steger, et al.

(2015). Cornea 34(11): 1459-1465.

Corneal angiography for guiding and evaluating fine-needle diathermy treatment of corneal neovascularization.

Spiteri, N., V. Romano, et al.

(2015). Ophthalmology 122(6): 1079-1084.

Pharmacokinetics of Meropenem for Use in Bacterial Keratitis Pharmacokinetics of Meropenem.

Sueke, H., S. Kaye, et al.

(2015). Investigative ophthalmology & visual science 56(10): 5731-5738.

Fast segmentation of anterior segment optical coherence tomography images using graph cut.

Williams, D., Y. Zheng, et al.

(2015). Eye and Vision 2(1): 1.

Retinal vessel segmentation: An efficient graph cut approach with retinex and local phase.

Zhao, Y., Y. Liu, et al.

(2015). PloS one 10(4): e0122332.

Automated detection of vessel abnormalities on fluorescein angiogram in malarial retinopathy.

Zhao, Y., I. J. MacCormick, et al.

(2015). Scientific reports 5: 11154.

Automated detection of leakage in fluorescein angiography images with application to malarial retinopathy.

Zhao, Y., I. J. MacCormick, et al.

(2015). Scientific reports 5.

Automated vessel segmentation using infinite perimeter active contour model with hybrid region information with application to retinal images.

Zhao, Y., L. Rada, et al. (2015).

IEEE Transactions on Medical Imaging 34(9): 1797-1807.

Publications

2017

  1. OCT and layer segmentation: Lawman S, Williams BM, Zhang J, Shen YC, Zheng Y (2017). " Scan-less Line Field Optical Coherence Tomography, with automatic image segmentation, as a measurement tool for automotive coatings." Applied Sciences. To appear.
  2. Albarrak A, Coenen F, Zheng Y. Volumetric image classification using homogeneous decomposition and dictionary learning: A study using retinal optical coherence tomography for detecting age-related macular degeneration. Comput. Med. Imag. Grap. 2017; 55:113-123.
  3. Segmentation: Gao, Z., W. Bu, et al. (2017). "Automated layer segmentation of macular OCT images via graph-based SLIC superpixels and manifold ranking approach." Comput. Med. Imag. Grap. 55: 42-53.
  4. Vasculature segmentation: Zhao, Y., J. Zhao, et al. (2017). "Saliency driven vasculature segmentation with infinite perimeter active contour model." Neurocomputing.
  5. Leakage detection: Zhao, Y., Y. Zheng, et al. (2017). "Intensity and Compactness Enabled Saliency Estimation for Leakage Detection in Diabetic and Malarial Retinopathy." IEEE T. Med. Imaging 36(1): 51-63.

2016

  1. OCT: Dong, Y., S. Lawman, et al. (2016). "Nondestructive analysis of automotive paints with spectral domain optical coherence tomography." Applied optics 55(13): 3695-3700.
  2. OCT: Lawman, S., Y. Dong, et al. (2016). "High resolution corneal and single pulse imaging with line field spectral domain optical coherence tomography." Optics express 24(11): 12395-12405.
  3. 3D Reconstruction: Williams, D., Y. Zheng, et al. (2016). "Reconstruction of 3D surface maps from anterior segment optical coherence tomography images using graph theory and genetic algorithms." Biomed. Signal Process. Control 25: 91-98.
  4. Leakage Detection: Zhao, Y., P. Su, et al. (2016). "A compactness based saliency approach for leakages detection in fluorescein angiogram." International Journal of Machine Learning and Cybernetics: 1-9.

2015

  1. Measuring Choroidal Thickness: Boonarpha, N., Y. Zheng, et al. (2015). "Standardization of choroidal thickness measurements using enhanced depth imaging optical coherence tomography." Int. J. Ophthalmol. 8(3): 484.
  2. Blind Deconvolution: Chen, K., S. P. Harding, et al. (2015). "A new study of blind deconvolution with implicit incorporation of nonnegativity constraints." Int. J. Comput. Math. 2015.
  3. Romano, V., B. Steger, et al. (2015). "Angiographic and in vivo confocal microscopic characterization of human corneal blood and presumed lymphatic neovascularization: a pilot study." Cornea 34(11): 1459-1465.
  4. Spiteri, N., V. Romano, et al. (2015). "Corneal angiography for guiding and evaluating fine-needle diathermy treatment of corneal neovascularization." Ophthalmology 122(6): 1079-1084.
  5. Sueke, H., S. Kaye, et al. (2015). "Pharmacokinetics of Meropenem for Use in Bacterial KeratitisPharmacokinetics of Meropenem." Investigative ophthalmology & visual science 56(10): 5731-5738.
  6. Williams, D., Y. Zheng, et al. (2015). "Fast segmentation of anterior segment optical coherence tomography images using graph cut." Eye and Vision 2(1): 1.
  7. Vessel Segmentation: Zhao, Y., Y. Liu, et al. (2015). "Retinal vessel segmentation: An efficient graph cut approach with retinex and local phase." PloS one 10(4): e0122332.
  8. Zhao, Y., I. J. MacCormick, et al. (2015). "Automated detection of vessel abnormalities on fluorescein angiogram in malarial retinopathy." Scientific reports 5: 11154.
  9. Leakage Detection: Zhao, Y., I. J. MacCormick, et al. (2015). "Automated detection of leakage in fluorescein angiography images with application to malarial retinopathy." Scientific reports 5.
  10. Vessel Segmentation: Zhao, Y., L. Rada, et al. (2015). "Automated vessel segmentation using infinite perimeter active contour model with hybrid region information with application to retinal images." IEEE Transactions on Medical Imaging 34(9): 1797-1807.

Conference Talks

DeSE, Paris, France

14-16 June 2017

Al-Bander B, Williams BM, Al-Taee M, Al-Nuaimy W, Zheng Y: Choroid segmentation with deep learning

MIUA, Edinburgh, UK

11-13 July 2017

Pratt H, Williams BM, Ku J, Coenen F, Zheng Y: Automatic vessel detection and identification of retinal vessel junctions in colour fundus photography

CMIH, Liverpool, UK

27 July 2017

Williams BM: Automatic vessel detection and identification of retinal vessel junctions in colour fundus photography

OMIA4, Quebec City, Quebec

11-14 Sep 2017

Williams BM, Al-Bander B, Pratt H, Zhao Y, Zheng Y, Shen, Y: Fast Blur Detection and Parametric Deconvolution of Retinal Fundus Images

ECML, Skopje, Macedonia

18-22 Sep 2017

Pratt H, Williams BM, Coenen F, Zheng Y: FCNN: Fourier Convolutional Neural Networks