AIMC Topic: Lung Neoplasms
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Evaluate the Malignancy of Pulmonary Nodules Using the 3-D Deep Leaky Noisy-OR Network.
IEEE transactions on neural networks and learning systems
Feb 14, 2019
Automatic diagnosing lung cancer from computed tomography scans involves two steps: detect all suspicious lesions (pulmonary nodules) and evaluate the whole-lung/pulmonary malignancy. Currently, there are many studies about the first step, but few ab...
[The age of artificial intelligence in lung cancer pathology: Between hope, gloom and perspectives].
Annales de pathologie
Feb 13, 2019
Histopathology is the fundamental tool of pathology used for more than a century to establish the final diagnosis of lung cancer. In addition, the phenotypic data contained in the histological images reflects the overall effect of molecular alteratio...
Automatic Detection and Classification of Lung Nodules in CT Image Using Optimized Neuro Fuzzy Classifier with Cuckoo Search Algorithm.
Journal of medical systems
Feb 13, 2019
The Lung nodules are very important to indicate the lung cancer, and its early detection enables timely treatment and increases the survival rate of patient. Even though lots of works are done in this area, still improvement in accuracy is required f...
ECM-CSD: An Efficient Classification Model for Cancer Stage Diagnosis in CT Lung Images Using FCM and SVM Techniques.
Journal of medical systems
Feb 12, 2019
As is eminent, lung cancer is one of the death frightening syndromes among people in present cases. The earlier diagnosis and treatment of lung cancer can increase the endurance rate of the affected people. But, the structure of the cancer cell makes...
Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss.
Journal of healthcare engineering
Feb 4, 2019
Early detection and classification of pulmonary nodules using computer-aided diagnosis (CAD) systems is useful in reducing mortality rates of lung cancer. In this paper, we propose a new deep learning method to improve classification accuracy of pulm...
A Comparative Texture Analysis Based on NECT and CECT Images to Differentiate Lung Adenocarcinoma from Squamous Cell Carcinoma.
Journal of medical systems
Feb 1, 2019
The purpose of the study was to compare the texture based discriminative performances between non-contrast enhanced computed tomography (NECT) and contrast-enhanced computed tomography (CECT) images in differentiating lung adenocarcinoma (ADC) from s...
Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches.
IEEE transactions on medical imaging
Jan 23, 2019
Risk stratification (characterization) of tumors from radiology images can be more accurate and faster with computer-aided diagnosis (CAD) tools. Tumor characterization through such tools can also enable non-invasive cancer staging, prognosis, and fo...
Predicting radiation pneumonitis in locally advanced stage II-III non-small cell lung cancer using machine learning.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jan 23, 2019
BACKGROUND AND PURPOSE: Radiation pneumonitis (RP) is a radiotherapy dose-limiting toxicity for locally advanced non-small cell lung cancer (LA-NSCLC). Prior studies have proposed relevant dosimetric constraints to limit this toxicity. Using machine ...
Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence.
Biomedical engineering online
Jan 22, 2019
BACKGROUND: A deep learning computer artificial intelligence system is helpful for early identification of ground glass opacities (GGOs).
Humans
Radiographic Image Interpretation, Computer-Assisted
Algorithms
False Positive Reactions
Databases, Factual
Tomography, X-Ray Computed
Lung Neoplasms
Sensitivity and Specificity
Diagnosis, Computer-Assisted
Reproducibility of Results
Solitary Pulmonary Nodule
Lung
Deep Learning
Radiology
Image Processing, Computer-Assisted
Automatic lung nodule detection using multi-scale dot nodule-enhancement filter and weighted support vector machines in chest computed tomography.
PloS one
Jan 10, 2019
A novel CAD scheme for automated lung nodule detection is proposed to assist radiologists with the detection of lung cancer on CT scans. The proposed scheme is composed of four major steps: (1) lung volume segmentation, (2) nodule candidate extractio...
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