Universal encoding of pan-cancer histology by deep texture representations.
Sign Up to like & getrecommendations! Published in 2022 at "Cell reports"
DOI: 10.1016/j.celrep.2022.110424
Abstract: Cancer histological images contain rich biological and clinical information, but quantitative representation can be problematic and has prevented the direct comparison and accumulation of large-scale datasets. Here, we show successful universal encoding of cancer histology… read more here.
Keywords: cancer; histology deep; histology; universal encoding ... See more keywords
Conceptual data sampling for breast cancer histology image classification
Sign Up to like & getrecommendations! Published in 2017 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2017.07.018
Abstract: Data analytics have become increasingly complicated as the amount of data has increased. One technique that is used to enable data analytics in large datasets is data sampling, in which a portion of the data… read more here.
Keywords: technique; data sampling; cancer histology; breast cancer ... See more keywords
Multiplex Cellular Communities in Multi-Gigapixel Colorectal Cancer Histology Images for Tissue Phenotyping
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2020.3023795
Abstract: In computational pathology, automated tissue phenotyping in cancer histology images is a fundamental tool for profiling tumor microenvironments. Current tissue phenotyping methods use features derived from image patches which may not carry biological significance. In… read more here.
Keywords: multiplex cellular; cellular communities; histology; cancer histology ... See more keywords