AIMC Topic: Lung Neoplasms
Clear Filters Showing 1181 to 1190 of 1635 articles
Simultaneous cosegmentation of tumors in PET-CT images using deep fully convolutional networks.
Medical physics
Jan 4, 2019
PURPOSE: To investigate the use and efficiency of 3-D deep learning, fully convolutional networks (DFCN) for simultaneous tumor cosegmentation on dual-modality nonsmall cell lung cancer (NSCLC) and positron emission tomography (PET)-computed tomograp...
Segmenting lung tumors on longitudinal imaging studies via a patient-specific adaptive convolutional neural network.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 31, 2018
PURPOSE: To design a deep learning algorithm that automatically delineates lung tumors seen on weekly magnetic resonance imaging (MRI) scans acquired during radiotherapy and facilitates the analysis of geometric tumor changes.
Predictors of Nodal and Metastatic Failure in Early Stage Non-small-cell Lung Cancer After Stereotactic Body Radiation Therapy.
Clinical lung cancer
Dec 29, 2018
INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) undergoing stereotactic body radiation therapy (SBRT) develop metastases, which is associated with poor outcomes. We sought to identify factors predictive o...
An IoT Based Predictive Modelling for Predicting Lung Cancer Using Fuzzy Cluster Based Segmentation and Classification.
Journal of medical systems
Dec 18, 2018
In this paper, we propose a new Internet of Things (IoT) based predictive modelling by using fuzzy cluster based augmentation and classification for predicting the lung cancer disease through continuous monitoring and also to improve the healthcare b...
Multi-Institutional Validation of a Knowledge-Based Planning Model for Patients Enrolled in RTOG 0617: Implications for Plan Quality Controls in Cooperative Group Trials.
Practical radiation oncology
Dec 15, 2018
PURPOSE: This study aimed to evaluate the feasibility of using a single-institution, knowledge-based planning (KBP) model as a dosimetric plan quality control (QC) for multi-institutional clinical trials. The efficacy of this QC tool was retrospectiv...
Initial results of pulmonary resection after neoadjuvant nivolumab in patients with resectable non-small cell lung cancer.
The Journal of thoracic and cardiovascular surgery
Dec 13, 2018
OBJECTIVE: We conducted a phase I trial of neoadjuvant nivolumab, a monoclonal antibody to the programmed cell death protein 1 checkpoint receptor, in patients with resectable non-small cell lung cancer. We analyzed perioperative outcomes to assess t...
Isolated Pulmonary Cryptococcosis Confused with Lung Tumor 5 Years After Kidney Transplantation: A Case Report.
Transplantation proceedings
Dec 12, 2018
BACKGROUND: In transplant recipients, due to the use of immunosuppressive therapy, it is occasionally difficult to distinguish between an infection and malignancy, especially in the case of a lung lesion. Here, we report a case of isolated pulmonary ...
Incorporating automatically learned pulmonary nodule attributes into a convolutional neural network to improve accuracy of benign-malignant nodule classification.
Physics in medicine and biology
Dec 10, 2018
Existing deep-learning-based pulmonary nodule classification models usually use images and benign-malignant labels as inputs for training. Image attributes of the nodules, as human-nameable high-level semantic labels, are rarely used to build a convo...
Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study.
PLoS medicine
Nov 30, 2018
BACKGROUND: Non-small-cell lung cancer (NSCLC) patients often demonstrate varying clinical courses and outcomes, even within the same tumor stage. This study explores deep learning applications in medical imaging allowing for the automated quantifica...
Radiographic Image Interpretation, Computer-Assisted
Preliminary Data
Lung Neoplasms
Carcinoma, Non-Small-Cell Lung
Predictive Value of Tests
Neoplasm Staging
Risk Assessment
Diagnosis, Computer-Assisted
Deep Learning
Female
Reproducibility of Results
Risk Factors
Aged
Humans
Aged, 80 and over
Retrospective Studies
Adult
Tomography, X-Ray Computed
Male
Clinical Decision-Making
Middle Aged
Deep Semi Supervised Generative Learning for Automated Tumor Proportion Scoring on NSCLC Tissue Needle Biopsies.
Scientific reports
Nov 26, 2018
The level of PD-L1 expression in immunohistochemistry (IHC) assays is a key biomarker for the identification of Non-Small-Cell-Lung-Cancer (NSCLC) patients that may respond to anti PD-1/PD-L1 treatments. The quantification of PD-L1 expression current...
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