AI in Radiology and Radiomics 101: Resources and Roadmap
I have a lot of colleagues who want to learn AI to improve their radiology practice. They frequently ask me how to…
Artificial Intelligence
NVIDIA MAISI: Generate Synthetic CT Images with AI
NVIDIA MAISI can generate synthetic 3D CT images up to 512×512×768 voxels that are indistinguishable from real scans. Here’s how this breakthrough…
Radiology Datasets for AI Model Training
RSNA STR Chest CT Pulmonary Embolism Detection Dataset This dataset comprises 1,937,450 DICOM images (totaling 980.24 GB) drawn from 7,279 training studies,…
What is Distilled and Quantized Models?
Researchers make advancements in machine learning every day, and I recently explored two of them: distillation and quantization. While I was familiar…
ViT vs CNN: Vision Transformers and Convolutional Neural Networks in Medical Image Analysis
I read this article today and took some notes. I want to mention it here for my future work and to look…
Breast Ultrasound Lesion Classification with PyRadiomics and Scikit-Learn
In the previous post, we explored Radiomics and its Workflow step-by-step. Radiomics is a powerful tool for quantifying imaging features from medical images to extract clinically…
Introduction to Radiomics with Python
What is Radiomics? Radiomics is a field at the intersection of medical imaging and data science that focuses on extracting large quantities…
NVIDIA Holoscan and IGX Orin: Getting Started
I recently had the chance to attend a webinar organized by PNY that focused on industrial and medical edge AI, featuring NVIDIA…
What is Vector Store Optimization?
In the rapidly advancing world of AI, especially with the growth of Large Language Models (LLMs), a new term has emerged for…
