AIMC Topic: Lung Neoplasms

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Functional-guided radiotherapy using knowledge-based planning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring co...

A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.

Medical physics
PURPOSE: The automatic detection of pulmonary nodules using CT scans improves the efficiency of lung cancer diagnosis, and false-positive reduction plays a significant role in the detection. In this paper, we focus on the false-positive reduction tas...

Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening.

Physics in medicine and biology
Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive pr...

Agile convolutional neural network for pulmonary nodule classification using CT images.

International journal of computer assisted radiology and surgery
OBJECTIVE: To distinguish benign from malignant pulmonary nodules using CT images is critical for their precise diagnosis and treatment. A new Agile convolutional neural network (CNN) framework is proposed to conquer the challenges of a small-scale m...

Role of artificial intelligence in the care of patients with nonsmall cell lung cancer.

European journal of clinical investigation
BACKGROUND: Lung cancer is the leading cause of cancer death worldwide. In up to 57% of patients, it is diagnosed at an advanced stage and the 5-year survival rate ranges between 10%-16%. There has been a significant amount of research using machine ...

An expert system design to diagnose cancer by using a new method reduced rule base.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: A Medical Expert System (MES) was developed which uses Reduced Rule Base to diagnose cancer risk according to the symptoms in an individual. A total of 13 symptoms were used. With the new MES, the reduced rules are controll...

A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning.

BioMed research international
Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma b...

A singular value decomposition linear programming (SVDLP) optimization technique for circular cone based robotic radiotherapy.

Physics in medicine and biology
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendo...

Lung Lesion Detection in CT Scan Images Using the Fuzzy Local Information Cluster Means (FLICM) Automatic Segmentation Algorithm and Back Propagation Network Classification.

Asian Pacific journal of cancer prevention : APJCP
Lung cancer is a frequently lethal disease often causing death of human beings at an early age because of uncontrolled cell growth in the lung tissues. The diagnostic methods available are less than effective for detection of cancer. Therefore an aut...