Name: Wahidul Alam
Type: User
Company: The University of Iowa
Bio: Biomedical Engineering PhD student at UIOWA | Inverse Problems | Computational Imaging | Machine Learning | MRI
Location: Iowa City, Iowa, United States
Blog: https://github.com/wahidul-alam
Wahidul Alam's Projects
Materials for the "Efficient Forward Models for Image Reconstruction" educational talk at the 2023 ISMRM Annual Meeting.
We develop a 16 channel flexible and anatomy conforming coil to provide localized sensitivity over upper and infra glottic airway regions of interest. In this work, imaging capabilities of the custom coil is compared against existing head only, and head neck coils.
Jupyter notebooks associated with the Algorithms for Optimization textbook
This repo includes ChatGPT prompt curation to use ChatGPT better.
BM3D denoising method implementation on Python
An un-trained neural network with a potential application in accelerated MRI
This repo is for the Linkedin Learning course: Level up: C++
In this course project, we have demonstrated the application of super-resolution in accelerated MRI reconstruction to improve image quality and speed.
In this course project, we segment and classify washers of different sizes and colors using classical digital image processing algorithms.
The implementation of Graph Image Prior (GIP) for Unsupervised Dynamic MRI Reconstruction
Image Classification Using Vision transformer from Scractch
In this group project of deep-learning course, we demonstrate implementation of CycleGan on upper airway and brain imaging. By applying GAN, we generate synthetic T2 weighted image from T1 weighted images.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
In this course project of the Machine Learning-I, the goal is to classify natural images in the CIFAR-10 dataset. In part-1, we have developed a SVM based classifier with 10 classes. Next, we have replaced the SVM with CNN based multi-class classifier to improve accuracy.
Hub for open-source MR-related software
An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.
In this class project, we first train a U-Net network for region-specific segmentation. Next, apply support vector machines and its ensembles on the extracted features of U-NET encoder for a binary classification problem
Calls ChatGPT to make an itinerary and then uses Google Maps to get directions. Makes a map of the result
Uncertainty Guided Progressive GANs for Medical Image Translation
https://arxiv.org/abs/2008.13065