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• W2161507325 abstract "Electron tomography (ET) is a powerful tool for quantitatively mapping the complex 3D sub-cellular structures of cells. High accuracy segmentation results are great value to cell biologists. They facilitate the comparison processes across statistically significant datasets of properties or structure information like size/volume of cellular compartments. Manual segmentation is reasonably accurate but the process might be too slow – since the accuracy is highly dependent on the training of the person conducting the task. Automated segmentation therefore opens a number of opportunities. But these automated methods must be fast and capable of accurately delineating all contours of interest, ideally at organelle and molecular level – where many of which were reportedly not successful on ET datasets. Semiautomated approaches however have substantially allowed wider scope in resulting maintained cellular membrane tracing quality and accuracy and providing improved segmentation time. These reasons have motivated the development of a pipeline – semi-automated cellular tomogram segmentation workflow (CTSW) with particular components – that will find the best settings of chosen combination methods for high resolution tomogram segmentation specific to the intrinsic properties of the image volume being processed. The study also introduced a set of scoring objectives to enable timely segmentation of cellular compartments and expedite the process of optimizing method settings." @default.
• W2161507325 created "2016-06-24" @default.
• W2161507325 creator A5062884572 @default.
• W2161507325 date "2014-01-01" @default.
• W2161507325 modified "2023-09-27" @default.
• W2161507325 title "Semi-Automated Cellular Tomogram Segmentation Workflow (CTSW): Towards an Automatic Target-Scoring System" @default.
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