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How Artificial Intelligence Enhances Confocal Imaging
In this article, we show how artificial intelligence (AI) can enhance your imaging experiments. Namely, how Dynamic Signal Enhancement powered by Aivia improves image quality while capturing the…
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Spectroscopic Evaluation of Red Blood Cells
Hemoglobinopathies are a major healthcare problem. This study presents a possible diagnostic tool for thalassemia which is based on confocal spectroscopy. This approach exploits spectral detection and…
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Visualizing Protein Degradation and Aggregation in the Living Cell
Our guest speaker, Prof Dr Eric Reits, presents his work on neurodegenerative disorders. Reits’ group are experts on the subject of Huntington’s disease and work towards identifying leads for…
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Life Beyond the Pixels: Deep Learning Methods for Single Cell Analysis
Our guest speaker Prof Dr Peter Horvath presents his work on single cell-based large-scale microscopy experiments. This novel targeting approach includes the use of machine learning models and…
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Tissue Image Gallery
Visual analysis of animal and human tissues is critical to understand complex diseases such as cancer or neurodegeneration. From basic immunohistochemistry to intravital imaging, confocal microscopy…
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Adding Dimensions to Multiplex Molecular Imaging
Molecular imaging of living specimens offers a means to draw upon the growing body of high-throughput molecular data to better understand the underlying cellular and molecular mechanisms of complex…
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Benefits of TauContrast to Image Complex Samples
In this interview, Dr. Timo Zimmermann talks about his experience with the application of TauSense tools and their potential for the investigation of demanding samples such as thick samples or…
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How Can Immunofluorescence Aid Virology Research?
Modern virology research has become as crucial now as ever before due to the global COVID-19 pandemic. There are many powerful technologies and assays that virologists can apply to their research into…
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LIGHTNINGによって試料から最大限の情報を引き出す
LIGHTNINGは、他の方法では簡単に可視化できない、微細な構造や形態を完全自動で明らかにする、適応能力に優れた情報抽出プロセスです。 LIGHTNINGは、画像全体を同一のパラメーターで演算する従来型の手法とは異なり、ボクセル(3次元画素)ごとに適切なパラメーターを算出することによって、最高の忠実度であらゆる微細形態を明らかにします。