Results 151 to 160 of about 295,660 (323)
U-Net-and-a-half: Convolutional network for biomedical image segmentation using multiple expert-driven annotations [PDF]
Yichi Zhang +10 more
openalex +1 more source
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
An automatic COVID-19 CT segmentation based on U-Net with attention mechanism [PDF]
Tongxue Zhou, Stéphane Canu, Su Ruan
openalex
Multi-Encoder U-Net for Automatic Kidney Tumor Segmentation [PDF]
Xueying Chen, Chao Xu
openalex +1 more source
Dimethyl fumarate (DMF) reduces growth of HPV‐positive cervical cancer spheroids and induces ferroptosis in cervical cancer cells via blocking SLC7A11/Glutathione (GSH) axis. Combination of subcytotoxic doses of DMF and cisplatin (CDDP) further suppresses spheroid growth and drives cell death in 2D culture models.
Carolina Punziano +6 more
wiley +1 more source
MRI-based automatic segmentation of rectal cancer using 2D U-Net on two independent cohorts [PDF]
Franziska Knuth +14 more
openalex +1 more source
Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma
Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra +6 more
wiley +1 more source
IMAGE SEGMENTATION ACCURACY DEPENDING ON THE DEPTH OF U-NET MODEL
Jevģēnijs Riekstiņš, Sergejs Kodors
openalex +2 more sources
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
wiley +1 more source
Temporal Autoencoder with U-Net Style Skip-Connections for Frame Prediction [PDF]
Jay Santokhi +4 more
openalex +1 more source

