Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.

AI tools like Google’s Veo 3 and Runway can now create strikingly realistic video. WSJ’s Joanna Stern and Jarrard Cole put them to the test in a film made almost entirely with AI. Watch the film and ...

OpenAI is rolling out a new version of ChatGPT Images that promises better instruction-following, more precise editing, and up to 4x faster image generation speeds. The new model, dubbed GPT Image 1.5 ...

Software built into the cameras on iPhones and Android phones makes quick work of decoding QR codes. How do you do that on a laptop or desktop computer? I have a friend who calls me occasionally to ...

This is the PyTorch implementation of our MICCAI 2024 paper "Robust Semi-Supervised Multimodal Medical Image Segmentation via Cross Modality Collaboration" by Xiaogen Zhou, Yiyou Sun, Min Deng, Winnie ...

The wrapper consistently crashes with segmentation fault (exit code -11) when attempting to access most topics from a ZED X One GS camera. The component initializes successfully and connects to the ...

Abstract: Medical image segmentation is critical for disease diagnosis and treatment assessment. However, concerns regarding the reliability of segmentation regions persist among clinicians, mainly ...