Publications

• Ma D, Kumar M, Khetan V, Sen P, Bhende M, Chen S, et al. Clinical explainable differential diagnosis of polypoidal choroidal vasculopathy and age-related macular degeneration using deep learning. Comput Biol Med. 2022 Feb 14;143:105319.
• Yee E, Ma D, Popuri K, Chen S, Lee H, Chow V, et al. 3D hemisphere-based convolutional neural network for whole-brain MRI segmentation. Comput Med Imaging Graph. 2022 Jan;95:102000.
• Shi H, Ma D, Faisal Beg M, Cao J. A functional proportional hazard cure rate model for interval-censored data. Stat Methods Med Res. 2022 Jan;31(1):154–68.
• Mirabnahrazam G, Ma D, Lee S, Popuri K, Lee H, Cao J, et al. Machine Learning Based Multimodal Neuroimaging Genomics Dementia Score for Predicting Future Conversion to Alzheimer’s Disease. J Alzheimers Dis. 2022;87(3):1345–65.
• Ma D, Yee E, Stocks JK, Jenkins LM, Popuri K, Chausse G, et al. Blinded Clinical Evaluation for Dementia of Alzheimer’s Type Classification Using FDG-PET: A Comparison Between Feature-Engineered and Non-Feature-Engineered Machine Learning Methods. J Alzheimers Dis. 2021;80(2):715–26.
• Ma D, Lu D, Chen S, Heisler M, Dabiri S, Lee S, et al. LF-UNet - A novel anatomical-aware dual-branch cascaded deep neural network for segmentation of retinal layers and fluid from optical coherence tomography images. Comput Med Imaging Graph. 2021 Dec;94:101988.
• Yu TT, Ma D, Lo J, Ju MJ, Beg MF, Sarunic MV. Effect of optical coherence tomography and angiography sampling rate towards diabetic retinopathy severity classification. Biomed Opt Express. 2021 Oct 1;12(10):6660–73.
• Yee E, Ma D, Popuri K, Wang L, Beg MF. Construction of MRI-Based Alzheimer’s Disease Score Based on Efficient 3D Convolutional Neural Network: Comprehensive Validation on 7,902 Images from a Multi-Center Dataset. J Alzheimers Dis. 2021;79(1):47–58.
• Shi H, Ma D, Nie Y, Faisal Beg M, Pei J, Cao J, et al. Early diagnosis of Alzheimer’s disease on ADNI data using novel longitudinal score based on functional principal component analysis. J Med Imaging (Bellingham). 2021 Mar;8(2):024502.
• Ma D, Lu D, Popuri K, Wang L, Beg MF. Differential Diagnosis of Frontotemporal Dementia, Alzheimer’s Disease, and Normal Aging Using a Multi-Scale Multi-Type Feature Generative Adversarial Deep Neural Network on Structural Magnetic Resonance Images. Front Neurosci. 2020;14:853.
• Ma D, Cardoso MJ, Zuluaga MA, Modat M, Powell NM, Wiseman FK, et al. Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellar cortex of the Tc1 mouse model of down syndrome - a comprehensive morphometric analysis with active staining contrast- enhanced MRI. Neuroimage. 2020 Dec;223:117271.
• Ma D, Lu D, Heisler M, Dabiri S, Lee S, Ding GW, Sarunic MV, Beg MF. Cascade dual-branch deep neural networks for retinal layer and fluid segmentation of optical coherence tomography incorporating relative positional map. InMedical Imaging with Deep Learning 2020 Sep 21 (pp. 493-502). PMLR.
• Miao Y, Siadati M, Song J, Ma D, Jian Y, Beg MF, et al. Phase-corrected buffer averaging for enhanced OCT angiography using FDML laser. Opt Lett. 2021 Aug 15;46(16):3833–6.
• Sidiqi A, Wahl D, Lee S, Ma D, To E, Cui J, et al. In vivo Retinal Fluorescence Imaging With Curcumin in an Alzheimer Mouse Model. Front Neurosci. 2020;14:713.
• Popuri K, Ma D, Wang L, Beg MF. Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer’s disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases. Hum Brain Mapp. 2020 Oct 1;41(14):4127–47.
• Wang L, Heywood A, Stocks J, Bae J, Ma D, Popuri K, et al. Grant Report on PREDICT-ADFTD: Multimodal Imaging Prediction of AD/FTD and Differential Diagnosis. J Psychiatr Brain Sci. 2019;4:e190017.
• Ma D, Popuri K, Bhalla M, Sangha O, Lu D, Cao J, et al. Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database. Hum Brain Mapp. 2019 Apr 1;40(5):1507–27.
• Ma D, Holmes HE, Cardoso MJ, Modat M, Harrison IF, Powell NM, et al. Study the Longitudinal in vivo and Cross-Sectional ex vivo Brain Volume Difference for Disease Progression and Treatment Effect on Mouse Model of Tauopathy Using Automated MRI Structural Parcellation. Front Neurosci. 2019;13:11.
• Harrison IF, Whitaker R, Bertelli PM, O’Callaghan JM, Csincsik L, Bocchetta M, et al. Optic nerve thinning and neurosensory retinal degeneration in the rTg4510 mouse model of frontotemporal dementia. Acta Neuropathol Commun. 2019 Jan 7;7(1):4.
• Harrison IF, Whitaker R, Bertelli PM, O’Callaghan JM, Csincsik L, Wells JA, et al. Correction to: Optic nerve thinning and neurosensory retinal degeneration in the rTg4510 mouse model of frontotemporal dementia. Acta Neuropathol Commun. 2019 Aug 5;7(1):127.
• Holmes HE, Powell NM, Ma D, Ismail O, Harrison IF, Wells JA, et al. Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy. Front Neuroinform. 2017;11:20.
• Steventon JJ, Trueman RC, Ma D, Yhnell E, Bayram-Weston Z, Modat M, et al. Longitudinal in vivo MRI in a Huntington’s disease mouse model: Global atrophy in the absence of white matter microstructural damage. Sci Rep. 2016 Sep 1;6:32423.
• Powell NM, Modat M, Cardoso MJ, Ma D, Holmes HE, Yu Y, et al. Fully-Automated muMRI Morphometric Phenotyping of the Tc1 Mouse Model of Down Syndrome. PLoS One. 2016;11(9):e0162974.
• Holmes HE, Colgan N, Ismail O, Ma D, Powell NM, O’Callaghan JM, et al. Imaging the accumulation and suppression of tau pathology using multiparametric MRI. Neurobiol Aging. 2016 Mar;39:184–94.
• Ma D, Li KKW, Chan KC, Wu EX, Wong DSH. Distribution of Triamcinolone Acetonide after Intravitreal Injection into Silicone Oil-Filled Eye. Biomed Res Int. 2016;2016:5485467.
• Ma D, Cardoso MJ, Zuluaga MA, Modat M, Powell N, Wiseman F, Tybulewicz V, Fisher E, Lythgoe MF, Ourselin S. Grey matter sublayer thickness estimation in the mouse cerebellum. InInternational Conference on Medical Image Computing and Computer-Assisted Intervention 2015 Oct 5 (pp. 644-651). Springer, Cham.
• Ma D, Cardoso MJ, Modat M, Powell N, Wells J, Holmes H, et al. Automatic structural parcellation of mouse brain MRI using multi-atlas label fusion. PLoS One. 2014;9(1):e86576.

• Williams RL, Kearns VR, Lo AC, Day M, Garvey MJ, Krishna Y, et al. Novel heavy tamponade for vitreoretinal surgery. Invest Ophthalmol Vis Sci. 2013 Nov 5;54(12):7284–92.

  You can also find my articles on my Google Scholar profile.