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- W3127597810 abstract "Retinal Pigment Epithelium (RPE) cell implant manufacturing is one such avenue where there is a requirement for a quick implant assessment method for quality monitoring along its long-duration manufacturing process. Segmenting cell regions and contours from the implant absorbance image can help assess the implant’s quality. In this work, we propose a segmentation network which incorporates a novel Multi-scale Feature Aggregation Block (MFAB) and an Intermediate Generation Selection Attention (IGSA) module. The MFAB targets to provide a feature-rich representation of the input, and the IGSA module which generates multiple and diverse segmentation maps, learns to efficiently produce thefinal segmentation map with the help of attention coefficients. We extensively compare our proposed method on the Dice Similarity Coefficient and the Adjusted Rand Index metrics. Additionally, we experimentally validate the utility of the proposed IGSA module." @default.
- W3127597810 created "2021-02-15" @default.
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- W3127597810 date "2020-12-10" @default.
- W3127597810 modified "2023-09-27" @default.
- W3127597810 title "Intermediate Generation Selection Attention and Multi-scale Feature Aggregation for segmentation of cell regions in RPE implant absorbance images" @default.
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- W3127597810 doi "https://doi.org/10.1109/indicon49873.2020.9342342" @default.
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