AIMC Topic: Microscopy
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Tile-based microscopic image processing for malaria screening using a deep learning approach.
BMC medical imaging
Mar 22, 2023
BACKGROUND: Manual microscopic examination remains the golden standard for malaria diagnosis. But it is laborious, and pathologists with experience are needed for accurate diagnosis. The need for computer-aided diagnosis methods is driven by the enor...
Moving perfusion culture and live-cell imaging from lab to disc: proof of concept toxicity assay with AI-based image analysis.
Lab on a chip
Mar 14, 2023
, cell-based assays are essential in diagnostics and drug development. There are ongoing efforts to establish new technologies that enable real-time detection of cell-drug interaction during culture under flow conditions. Our compact (10 × 10 × 8.5 c...
Detection of malignancy in whole slide images of endometrial cancer biopsies using artificial intelligence.
PloS one
Mar 8, 2023
In this study we use artificial intelligence (AI) to categorise endometrial biopsy whole slide images (WSI) from digital pathology as either "malignant", "other or benign" or "insufficient". An endometrial biopsy is a key step in diagnosis of endomet...
Deep Learning Enhanced Electrochemiluminescence Microscopy.
Analytical chemistry
Mar 3, 2023
Limited by the efficiency of electrochemiluminescence, tens of seconds of exposure time are typically required to get a high-quality image. Image enhancement of short exposure time images to obtain a well-defined electrochemiluminescence image can me...
AtomVision: A Machine Vision Library for Atomistic Images.
Journal of chemical information and modeling
Mar 1, 2023
Computer vision techniques have immense potential for materials design applications. In this work, we introduce an integrated and general-purpose AtomVision library that can be used to generate and curate microscopy image (such as scanning tunneling ...
Optofluidic imaging meets deep learning: from merging to emerging.
Lab on a chip
Mar 1, 2023
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a quantitative "smart" engine. A suite of advanced optical microsco...
Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint.
PloS one
Feb 24, 2023
Diatoms represent one of the morphologically and taxonomically most diverse groups of microscopic eukaryotes. Light microscopy-based taxonomic identification and enumeration of frustules, the silica shells of these microalgae, is broadly used in aqua...
Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases.
Pathology, research and practice
Feb 6, 2023
Infectious diseases still threaten the global community, especially in resource-limited countries. An accurate diagnosis is paramount to proper patient and public health management. Identification of many microbes still relies on manual microscopic e...
A practical guide to deep-learning light-field microscopy for 3D imaging of biological dynamics.
STAR protocols
Jan 29, 2023
Here, we present a step-by-step protocol for the implementation of deep-learning-enhanced light-field microscopy enabling 3D imaging of instantaneous biological processes. We first provide the instructions to build a light-field microscope (LFM) capa...
Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence.
Journal of visualized experiments : JoVE
Jan 27, 2023
The micronucleus (MN) assay is used worldwide by regulatory bodies to evaluate chemicals for genetic toxicity. The assay can be performed in two ways: by scoring MN in once-divided, cytokinesis-blocked binucleated cells or fully divided mononucleated...
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