… in pathology image analysis, with an emphasis on lung cancer. Results: We outlined the
current challenges and opportunities in lung cancer pathology image … pathology in lung cancer, …

… Furthermore, the goal of this study was to show the feasibility of pathological image
analysis for the prognosis of lung cancer, and only existing TCGA data were used in this study. …

… Pathology images capture tumor histomorphological details … of tumor regions in pathology
images is labor intensive and … recognition system for lung cancer pathology images. From the …

… Although this tool was developed in lung adenocarcinoma pathology images, our results …
and neck cancer, breast cancer, and lung cancer squamous cell carcinoma pathology image …

… quantitative image … image features can predict the prognosis of lung cancer patients and
thereby contribute to precision oncology. Our methods are extensible to histopathology images …

… Traditionally, the pathological type of lung cancer requires a histopathological examination
… the pathological type of lung cancer via CT images. Due to the low amount of CT images in …

… -image data integration framework for lung cancer survival analysis. Due to the heterogeneity
of the lung cancer, we conduct our experiment in ADC lung cancer … cal image information, …

… The applications of digital pathology are expanding, from supporting remote institutes … lung
cancer. Through practice and research large archival databases of digital pathology images …

… CAD methods to pathological images have been conducted [4–… pathology images. Ojansivu
et al. [6] investigated automated classification of breast cancer from histopathological images…

… Several deep learning models for lung cancer pathology image analysis have been
proposed for lung cancer H&E-stained pathology images. Furthermore, several deep learning …