Cell Maps Representation For Lung Adenocarcinoma Growth Patterns Classification In Whole Slide Images

arXiv:2311.15847v2 Announce Type: replace-cross
Abstract: Lung adenocarcinoma is a morphologically heterogeneous disease, characterized by five primary histologic growth patterns. The quantity of these patterns can be related to tumor behavior and has a significant impact on patient prognosis. In this work, we propose a novel machine learning pipeline capable of classifying tissue tiles into one of the five patterns or as non-tumor, with an Area Under the Receiver Operating Characteristic Curve (AUCROC) score of 0.97. Our model's strength lies in …

abstract arxiv behavior classification cs.cv cs.lg disease eess.iv five growth images impact machine machine learning maps novel patient patterns replace representation type work