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U-Net: deep learning for cell counting, detection, and morphometry

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A novel deep learning-based 3D cell segmentation framework for

High-throughput label-free cell detection and counting from

DeepCAN: A Modular Deep Learning System for Automated Cell

Misic, a general deep learning-based method for the high

Frontiers Code-Free Development and Deployment of Deep Segmentation Models for Digital Pathology

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Automatic lesion detection and segmentation in 18F-flutemetamol positron emission tomography images using deep learning, BioMedical Engineering OnLine

U-Net Deep-Learning-Based 3D Cell Counter for the Quality Control

PDF) Quantitative Digital Microscopy with Deep Learning

Artificial Intelligence and Cellular Segmentation in Tissue Microscopy Images. - Abstract - Europe PMC

DeepBacs for multi-task bacterial image analysis using open-source

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Application of segmentation U-Net to human kidney biopsies. (A

Generalising from conventional pipelines using deep learning in high-throughput screening workflows

PDF] Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features