ArticleBiomedical optics express2022
Deep learning-based single-shot autofocus method for digital microscopy.
Article in Biomedical optics express, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 54 citations in OpenAlex.
- Real-time robust autofocus method enabling sustained intravital scanning light field imaging.Nature communications · 2026Article
- Digital defocus aberration interference for automated optical microscopy.Nature communications · 2026Article
- Deep Convolutional Neural Networks for Autofocus Control on aBiosensors · 2026Article
- Harnessing droplet microfluidics and morphology-based deep learning for the label-free study of polymicrobial-phage interactions.Communications biology · 2025Article
- A wavelet-guided transformer approach for autofocus in brightfield biological microscopy.Scientific reports · 2025Article
- Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm.Sensors (Basel, Switzerland) · 2025Article
- GJFocuser: a Gaussian difference and joint learning-based autofocus method for whole slide imaging.Biomedical optics express · 2025Article
- Precision autofocus in optical microscopy with liquid lenses controlled by deep reinforcement learning.Microsystems & nanoengineering · 2024Article
- Research on the Method of Depth-Sensing Optical System Based on Multi-Layer Interface Reflection.Sensors (Basel, Switzerland) · 2024Article
- A large multi-focus dataset for white blood cell classification.Scientific data · 2024Article
- Deep Learning-Based Dynamic Region of Interest Autofocus Method for Grayscale Image.Sensors (Basel, Switzerland) · 2024Article
- A Normalized Absolute Values Adaptive Evaluation Function of Image Clarity.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital pathology is being transformed by artificial intelligence (AI)-based pathological diagnosis. One major challenge for correct AI diagnoses is to ensure the focus quality of captured images. Here, we propose a deep learning-based single-shot autofocus method for microscopy. We use a modified MobileNetV3, a lightweight network, to predict the defocus distance with a single-shot microscopy image acquired at an arbitrary image plane without secondary camera or additional optics. The defocus prediction takes only 9 ms with a focusing error of only ∼1/15 depth of field. We also provide implementation examples for the augmented reality microscope and the whole slide imaging (WSI) system. Our proposed technique can perform real-time and accurate autofocus which will not only support pathologists in their daily work, but also provide potential applications in the life sciences, material research, and industrial automatic detection.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.