eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
The American Journal of Managed Care

Convolutional Neural Network Improves MS Lesion Segmentation

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, ...

7 Bell Labs Breakthroughs Honored as IEEE Milestones

Bell Labs is already highly recognized, but in its centennial year, the organization hoped to add more awards to burnish its ...
Labmate Online

ELRIG 2025: How Novo Nordisk is showing label-free route to functional phenotyping in brightfield high-content imaging

At ELRIG 2025 Dr Barak Gilboa of Novo Nordisk unveiled a suite of AI-enabled approaches that turn brightfield microscopy from ...
IEEE

LFIC-DRASC: Deep Light Field Image Compression Using Disentangled Representation and Asymmetrical Strip Convolution

Abstract: Light-Field (LF) image is emerging 4D data of light rays that is capable of realistically presenting spatial and angular information of 3D scene. However, the large data volume of LF images ...
IEEE

Robust Deep Convolutional Dictionary Model With Alignment Assistance for Multi-Contrast MRI Super-Resolution

Abstract: Multi-contrast magnetic resonance imaging (MCMRI) super-resolution (SR) methods aims to leverage the complementary information present in multi-contrast images. However, existing methods ...