Deep learning models for gastric signet ring cell carcinoma classification in whole slide images

11/18/2020

∙

Signet ring cell carcinoma (SRCC) of the stomach is a rare type of cancer with a slowly rising incidence. It tends to be more difficult to detect by pathologists mainly due to its cellular morphology and diffuse invasion manner, and it has poor prognosis when detected at an advanced stage. Computational pathology tools that can assist pathologists in detecting SRCC would be of a massive benefit. In this paper, we trained deep learning models using transfer learning, fully-supervised learning, and weakly-supervised learning to predict SRCC in Whole Slide Images (WSIs) using a training set of 1,765 WSIs. We evaluated the models on four different test sets of about 500 images each. The best model achieved a Receiver Operator Curve (ROC) area under the curve (AUC) of at least 0.99 on all four test sets, setting a top baseline performance for SRCC WSI classification.

READ FULL TEXT

Deep learning models for gastric signet ring cell carcinoma classification in whole slide images

Signet Ring Cell Detection With a Semi-supervised Learning Framework

Rapid Classification of Glaucomatous Fundus Images

A deep learning model for gastric diffuse-type adenocarcinoma classification in whole slide images

Glaucoma detection beyond the optic disc: The importance of the peripapillary region using explainable deep learning

A New Variational Model for Binary Classification in the Supervised Learning Context

Deep learning model trained on mobile phone-acquired frozen section images effectively detects basal cell carcinoma

A New Weakly Supervised Learning Approach for Real-time Iron Ore Feed Load Estimation

Deep learning models for gastric signet ring cell carcinoma classification in whole slide images

Related Research

Signet Ring Cell Detection With a Semi-supervised Learning Framework

Rapid Classification of Glaucomatous Fundus Images

A deep learning model for gastric diffuse-type adenocarcinoma classification in whole slide images

Glaucoma detection beyond the optic disc: The importance of the peripapillary region using explainable deep learning

A New Variational Model for Binary Classification in the Supervised Learning Context

Deep learning model trained on mobile phone-acquired frozen section images effectively detects basal cell carcinoma

A New Weakly Supervised Learning Approach for Real-time Iron Ore Feed Load Estimation