Compare deep learning cell segmentation tools Cellpose and StarDist: how each works, how they differ by imaging type, and ...
A new deep-learning model improved surgeons’ recognition of pelvic anatomy in video-based PLND tests, though live surgical ...
The field of orofacial medicine increasingly recognizes the temporomandibular joint (TMJ) as a complex anatomical and functional unit whose disorders can ...
Abstract: Multimodality medical imaging techniques have been increasingly applied in clinical practice and research studies. Corresponding multimodal image analysis and ensemble learning schemes have ...
Modern medical imaging increasingly relies on artificial intelligence to support detection, diagnosis, and prognostic ...
In this interview, AZoLife Sciences speaks with Boyd Butler, a microscopy and high-content screening expert at Molecular ...
The U.S. Deep Learning Market is Projected to Grow from $37.14 Billion in 2025 to $596.02 Billion by 2035, While Europe is ...
Researchers from Science Tokyo develop a Multi-scale Hessian-enhanced Patch-based Neural Network Model for Segmentation of Liver Tumor from CT Scans. Liver cancer is the sixth most common cancer ...
Abstract: Convolutional neural networks (CNNs) have achieved state-of-the-art performance for automatic medical image segmentation. However, they have not demonstrated sufficiently accurate and robust ...
We have developed an open-source software called bi-channel image registration and deep-learning segmentation (BIRDS) for the mapping and analysis of 3D microscopy data and applied this to the mouse ...
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