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

Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical researchers take when running a new study involving biomedical images. For ...

Turn photos into 3D with Meta's SAM 3D, using SAM 2 masks and Gaussian splatting, so you can build assets quickly for ...

A study has found that the way medical images are prepared before analysis can have a significant impact on the performance of deep learning models.

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To address the lack of suitable training data for deep-learning semantic segmentation models in urban landscaping, researchers developed a method that generates a training dataset without the need for ...