Automatic Volume

Automatic volume estimation, the process of computationally determining the size of 3D objects or regions within images, is a rapidly advancing field with applications across medicine, autonomous driving, and other domains. Current research emphasizes improving accuracy and efficiency through deep learning models, including neural radiance fields (NeRFs), convolutional neural networks (CNNs), and generative adversarial networks (GANs), often incorporating techniques like volume rendering and implicit neural representations to handle complex 3D data. These advancements are crucial for improving diagnostic accuracy in medical imaging, enhancing the capabilities of autonomous systems, and enabling more efficient analysis of large-scale datasets in various scientific disciplines.