AIMC Topic: Lung Neoplasms

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SPEQTACLE: An automated generalized fuzzy C-means algorithm for tumor delineation in PET.

Medical physics
PURPOSE: Accurate tumor delineation in positron emission tomography (PET) images is crucial in oncology. Although recent methods achieved good results, there is still room for improvement regarding tumors with complex shapes, low signal-to-noise rati...

Robotic-Assisted Thoracic Surgery for Early-Stage Lung Cancer: A Review.

AORN journal
This review evaluates the benefits and disadvantages associated with the use of robotic-assisted technology in performing lobectomies in patients with early-stage lung cancer. The author conducted a literature search of Ovid®, MEDLINE®, PubMed®, and ...

A method for volumetric imaging in radiotherapy using single x-ray projection.

Medical physics
PURPOSE: It is an intriguing problem to generate an instantaneous volumetric image based on the corresponding x-ray projection. The purpose of this study is to develop a new method to achieve this goal via a sparse learning approach.

Automatic learning-based beam angle selection for thoracic IMRT.

Medical physics
PURPOSE: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Int...

Comparison between target margins derived from 4DCT scans and real-time tumor motion tracking: insights from lung tumor patients treated with robotic radiosurgery.

Medical physics
PURPOSE: A unique capability of the CyberKnife system is dynamic target tracking. However, not all patients are eligible for this approach. Rather, their tumors are tracked statically using the vertebral column for alignment. When using static tracki...

Proposal of Local Automatic Weighing Attribute in CBIR.

Studies in health technology and informatics
Lung cancer is the most common malignant lesion and the principal cause of cancer-related death worldwide. This problem encourages researchers to build computer-aided solutions to help diagnose lung cancer. Content-based image retrieval (CBIR) system...

Multi-scale Convolutional Neural Networks for Lung Nodule Classification.

Information processing in medical imaging : proceedings of the ... conference
We investigate the problem of diagnostic lung nodule classification using thoracic Computed Tomography (CT) screening. Unlike traditional studies primarily relying on nodule segmentation for regional analysis, we tackle a more challenging problem on ...

Use of an Artificial Neural Network to Construct a Model of Predicting Deep Fungal Infection in Lung Cancer Patients.

Asian Pacific journal of cancer prevention : APJCP
BACKGROUND: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model anal...