Here, we contribute to the cancer imaging community through The Cancer Imaging Archive (TCIA) by providing investigator-initiated, same-day repeat CT scan images of 32 non鈥搒mall cell lung cancer (NSCLC) patients, along with radiologist-annotated lesion contours as a reference standard. Each ...
Due to the similarity between the training dataset and the testing dataset, as well as the morphological similarities in lung cancer, we have improved the Unet network based on the principle of similarity, thus enabling the precise demarcation of focal points. Download: Download high-res image (...
Efficient pre-processing and segmentation for lung cancer detection using fused CT images Electronics, 11 (1) (2021), p. 34 CrossrefGoogle Scholar 17. N. Garau, C. Paganelli, P. Summers, D. Bassis, C. Lanza A segmentation tool for pulmonary nodules in lung cancer screening: Testing and...
Automated detection and segmentation of non-small cell lung cancer computed tomography images Article Open access 14 June 2022 CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images Article Open access 17 May 2024 Introduction...
Welcome to Foundation Model for Lung Cancer CT images (FM-LCT). FM-LCT is a vertical foundation model for quantitative CT analysis in lung cancer. FM-LCT is trained on a diverse dataset covering various lung cancer types and stages, and it undergoes meticulous data preprocessing, ensuring optim...
Lung cancer represents a significant global health challenge, transcending demographic boundaries of age, gender, and ethnicity. Timely detection stands as
To evaluate the capability of PET/CT images for differentiating the histologic subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from radiomics-based machine learning/deep learning algorithms. Methods In this study, 867 patients with adenocarcinoma (ADC) and 552 patie...
Current studies indicate that fluorine-18-fluorodeoxyglucose positron emission tomography/ computed tomography ([18F]FDG PET/CT) is the most accurate imaging modality for the detection of relapsed locally advanced non-small cell lung cancer (NSCLC) after curatively intended chemoradiotherapy. To this day...
Tumor histology is an important predictor of therapeutic response and outcomes in lung cancer. Tissue sampling for pathologist review is the most reliable method for histology classification, however, recent advances in deep learning for medical image an
Lung cancer is considered more serious among other prevailing cancer types. One of the reasons for it is that it is usually not diagnosed until it has spread and by that time it becomes very difficult to treat. Early detection of lung cancer can signific