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ATCC
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LifePort Inc
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DeLano Scientific
pymol-generated superposition Pymol Generated Superposition, supplied by DeLano Scientific, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/caption+a7+a+survival+curves/pmc02253397-64-27-33?v=DeLano+Scientific Average 90 stars, based on 1 article reviews
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MiniMed Inc
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2026-07
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COMSOL Inc
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Carl Zeiss
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2026-07
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NeuroCom International
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Aerin Medical Inc
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Evaheart Inc
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Siemens AG
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2026-07
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KNIME GmbH
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2026-07
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ViewRay Inc
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Image Search Results
Journal: Frontiers in computer science
Article Title: Integration of the ImageJ Ecosystem in the KNIME Analytics Platform
doi: 10.3389/fcomp.2020.00008
Figure Lengend Snippet: Side-by-side comparison of ImageJ macro with KNIME workflow using KNIME Image Processing nodes.
Article Snippet: This requires correcting for possible rotations and misalignments between cameras, as well as for chromatic aberrations specific to each color channel. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 7:
Techniques: Comparison
Journal: Frontiers in computer science
Article Title: Integration of the ImageJ Ecosystem in the KNIME Analytics Platform
doi: 10.3389/fcomp.2020.00008
Figure Lengend Snippet: Quantitative analysis of subcellular structures. To analyze the consequences of disrupting the cytoskeleton on matrix adhesion focal adhesion complex formation is visualized using TIRF imaging. A KNIME workflow was leveraged to define the number of focal adhesion complexes at the periphery of the cell vs. within the center of the cell using sequential steps with discrete objectives: I. Read file in, II. Processing of the images into labels that capture the individual focal adhesion complexes, III. Arithmetic on the labels to obtain the characteristics (features) for classification, IV. Classification of the labels using extracted features, V. Visualization of the classified focal adhesion complexes (periphery vs center). Note that the output of this pipeline is a combination of visualization and quantitation. Both of these can be leveraged for further analysis.
Article Snippet: This requires correcting for possible rotations and misalignments between cameras, as well as for chromatic aberrations specific to each color channel. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 7:
Techniques: Imaging, Quantitation Assay
Journal: Frontiers in computer science
Article Title: Integration of the ImageJ Ecosystem in the KNIME Analytics Platform
doi: 10.3389/fcomp.2020.00008
Figure Lengend Snippet: Quantitative analysis of histological stain. The histological staining of a cell adhesion marker (CD166) related to tumor invasion and metastasis demonstrates significant variation across patient samples. As in user case #1, the KNIME workflow was divided into sequential steps that complete discrete objectives: 1) read in file , 2) pre-processing of the images and their annotation in preparation for analysis using ImageJ2 functionalities, 3) pixel classification using Weka-bases machine learning functionality, 4) post-classification processing of image data to labels that correspond to ‘positive’, 5) compilation of labels, images and annotations, 6) visualization of the quantitation by overlaying the labels with the original image.
Article Snippet: This requires correcting for possible rotations and misalignments between cameras, as well as for chromatic aberrations specific to each color channel. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 7:
Techniques: Staining, Marker, Quantitation Assay
Journal: Frontiers in computer science
Article Title: Integration of the ImageJ Ecosystem in the KNIME Analytics Platform
doi: 10.3389/fcomp.2020.00008
Figure Lengend Snippet: A KNIME workflow for channel-shift correction and particle tracking. The positions of bead detections are shown in three-pane scatter plots, before (left) and after (right) applying channel-shift correction. The density plots show absolute distances between apparent bead locations of two channels before (red) and after (cyan) correction.
Article Snippet: This requires correcting for possible rotations and misalignments between cameras, as well as for chromatic aberrations specific to each color channel. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 7:
Techniques:
Journal: The British Journal of Radiology
Article Title: Role and future of MRI in radiation oncology
doi: 10.1259/bjr.20180505
Figure Lengend Snippet: (a) ViewRay MRIdian system, (b) Elekta 1.5 T MRI-Linac, (c) Alberta’s Aurora RT system and (d) Australian (Sydney) MRI System, image courtesy of Paul Keall and Brad Oburn.
Article Snippet: 14,15,17–20 fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 2.
Techniques: