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šŸš€ Dave Le

Computer Vision Scientist (Researcher/Developer/Enthusiast)

I am a research engineer delving into deep neural networks for computer vision in medical imaging. All of my coding projects are developed in coordination with peer-reviewed publications for real-world applications. Currently, I am working on projects related to the classification of retinal diseases and the segmentation of retinal vessels in Optical Coherence Tomography (OCT) and OCT angiography (OCTA).

  • šŸ‘‹ There is an AI revolution on the horizon and I'm happy to be a part of it!
  • šŸ“§ If you have any questions, feel free to send an email@ [email protected].
  • šŸ”­ Iā€™m currently working on MF-AV-Net.

āš™ļø GitHub Statistics

šŸ’» Languages and Tools

TensorFlow Keras PyTorch

Python MATLAB R SQL HTML

NumPy OpenCV Pandas Matplotlib SciPy

Jupyter Visual Studios Sublime Spyder

Linux Windows







Research into OCT and OCTA

OCT and OCTA are advanced imaging techniques that provide fast, non-invasive, real-time, high-resolution, and 3D imaging. They offer numerous digital biomarkers that are useful for various applications. Although retinal imaging is the most common application of OCT and OCTA, they can also be used in other fields such as dermatology and dentistry. With a wealth of valuable data, OCT/OCTA can be readily applied in machine learning and deep learning tasks, including disease classification, image segmentation, and denoising.

Dave Le's Projects

adcnet icon adcnet

fully convolutional network for automated dispersion compensation in OCT images

awesome-matlab icon awesome-matlab

A curated list of awesome MATLAB toolboxes, applications, software and resources.

awesome-nlp icon awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

keras-gan icon keras-gan

Keras implementations of Generative Adversarial Networks.

mf-av-net icon mf-av-net

Multimodal Fusion for Deep Learning for Artery-Vein Segmentation using OCT and OCTA. The implementation is using Python and TensorFlow.

rnn icon rnn

Recurrent Neural Networks for Timeseries

svc-net icon svc-net

Deep learning for Spatial Vascular Connectivity Network (SVC-Net). The implementation is using Python and TensorFlow.

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