Du, W., Luo, X. and Chen, M. (2022) A Practical Deep Learning Model in Differentiating Pneumonia-Type Lung Carcinoma from Pneumonia on CT Images: Resnet Added with Attention Mechanism. Journal of Oncology, 2022, Article ID: 8906259.
https://doi.org/10.1155/2022/8906259

has been cited by the following article:

• TITLE: Advances in CT-Based Diagnosis of Pneumonic-Type Lung Cancer: A Review

  AUTHORS: Ya Liu, Yuanyi Huang

  KEYWORDS: Pneumonic-Type Lung Cancer, Computed Tomography, Photon-Counting Computed Tomography, Radiomics, Dual-Energy Computed Tomography

  JOURNAL NAME: Journal of Biosciences and Medicines, Vol.14 No.2, February 24, 2026

  ABSTRACT: Pneumonic-type lung cancer (PTLC) represents a distinct manifestation of lung carcinoma, characterized by overlapping clinical symptoms and imaging features with infectious lesions, often leading to misdiagnosis and delayed treatment upon initial imaging evaluation. Computed tomography (CT) is the primary imaging modality for pulmonary diseases. Therefore, accurate CT imaging diagnosis of PTLC holds significant value for clinical management. This review summarizes the applications and research progress of CT and CT-related imaging technologies in the diagnosis of PTLC.