Cargando…
Cell2Grid: an efficient, spatial, and convolutional neural network-ready representation of cell segmentation data
PURPOSE: Cell segmentation algorithms are commonly used to analyze large histologic images as they facilitate interpretation, but on the other hand they complicate hypothesis-free spatial analysis. Therefore, many applications train convolutional neural networks (CNNs) on high-resolution images that...
Autores principales: | Herbsthofer, Laurin, Tomberger, Martina, Smolle, Maria A., Prietl, Barbara, Pieber, Thomas R., López-García, Pablo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Photo-Optical Instrumentation Engineers
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709305/ https://www.ncbi.nlm.nih.gov/pubmed/36466076 http://dx.doi.org/10.1117/1.JMI.9.6.067501 |
Ejemplares similares
-
Influence of tumor-infiltrating immune cells on local control rate, distant metastasis, and survival in patients with soft tissue sarcoma
por: Smolle, Maria A, et al.
Publicado: (2021) -
Feature analysis of cell nuclear chromatin distribution in support of cervical cytology
por: Komagata, Hideki, et al.
Publicado: (2017) -
Automatic extraction of cell nuclei from H&E-stained histopathological images
por: Yi, Faliu, et al.
Publicado: (2017) -
Resolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networks
por: Bándi, Péter, et al.
Publicado: (2019) -
Recurrence analysis on prostate cancer patients with Gleason score 7 using integrated histopathology whole-slide images and genomic data through deep neural networks
por: Ren, Jian, et al.
Publicado: (2018)