Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective

S Huang, J Yang, N Shen, Q Xu, Q Zhao - Seminars in cancer biology, 2023 - Elsevier
Lung cancer is one of the malignant tumors with the highest incidence and mortality in the
world. The overall five-year survival rate of lung cancer is relatively lower than many leading …

[HTML][HTML] [18F] FDG-PET/CT radiomics and artificial intelligence in lung cancer: Technical aspects and potential clinical applications

R Manafi-Farid, E Askari, I Shiri, C Pirich… - Seminars in nuclear …, 2022 - Elsevier
Lung cancer is the second most common cancer and the leading cause of cancer-related
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …

Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space

M Fallahpoor, S Chakraborty, B Pradhan… - Computer methods and …, 2024 - Elsevier
Positron emission tomography/computed tomography (PET/CT) is increasingly used in
oncology, neurology, cardiology, and emerging medical fields. The success stems from the …

Near-infrared II semiconducting polymer dots: chain packing modulation and high-contrast vascular imaging in deep tissues

D Chen, W Qi, Y Liu, Y Yang, T Shi, Y Wang, X Fang… - ACS …, 2023 - ACS Publications
Fluorescence imaging in the second near-infrared (NIR-II) window has attracted
considerable interest in investigations of vascular structure and angiogenesis, providing …

AI-driven models for diagnosing and predicting outcomes in lung cancer: A systematic review and meta-analysis

M Kanan, H Alharbi, N Alotaibi, L Almasuood, S Aljoaid… - Cancers, 2024 - mdpi.com
Simple Summary This research explores the transformative potential of artificial intelligence
(AI) in the early detection of lung cancer. Through a comprehensive systematic review and …

Automatic Lung Cancer Segmentation in [18F]FDG PET/CT Using a Two-Stage Deep Learning Approach

J Park, SK Kang, D Hwang, H Choi, S Ha… - Nuclear medicine and …, 2023 - Springer
Purpose Since accurate lung cancer segmentation is required to determine the functional
volume of a tumor in [18F] FDG PET/CT, we propose a two-stage U-Net architecture to …

AI-based detection, classification and prediction/prognosis in medical imaging: towards radiophenomics

F Yousefirizi, P Decazes, A Amyar, S Ruan… - PET clinics, 2022 - pet.theclinics.com
The task of clinical interpretation of medical images starts with the scanning of the presented
image to detect the suspicious finding (“observation” in RadLex terminology (RID5) 1 which …

Detection of sub-centimeter lesions using digital TOF-PET/CT system combined with Bayesian penalized likelihood reconstruction algorithm

K Miwa, K Wagatsuma, R Nemoto… - Annals of Nuclear …, 2020 - Springer
Objective Many advances in PET/CT technology can potentially improve image quality and
the ability to detect small lesions. A new digital TOF-PET/CT scanner based on silicon …

Deep learning assisted contrast-enhanced CT–based diagnosis of cervical lymph node metastasis of oral cancer: a retrospective study of 1466 cases

X Xu, L **, L Wei, L Wu, Y Xu, B Liu, B Li, K Liu… - European …, 2023 - Springer
Objectives Lymph node (LN) metastasis is a common cause of recurrence in oral cancer;
however, the accuracy of distinguishing positive and negative LNs is not ideal. Here, we …

A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease management

N Anan, R Zainon, M Tamal - Insights into imaging, 2022 - Springer
Radiomics analysis quantifies the interpolation of multiple and invisible molecular features
present in diagnostic and therapeutic images. Implementation of 18-fluorine …