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The emergence of cloud infrastructure has the potential to provide significant benefits in a variety of areas in the medical imaging field. The driving force behind the extensive use of cloud infrastructure for medical image processing is the exponential increase in the size of computed tomography (CT) and magnetic resonance imaging (MRI) data. The size of a single CT/MRI image has increased manifold since the inception of these imagery techniques. This demand for the introduction of effective and efficient frameworks for extracting relevant and most suitable information (features) from these sizeable images. As early detection of lungs cancer can significantly increase the chances of survival of a lung scanner patient, an effective and efficient nodule detection system can play a vital role. In this article, we have proposed a novel classification framework for lungs nodule classification with less false positive rates (FPRs), high accuracy, sensitivity rate, less computationally expensive and uses a small set of features while preserving edge and texture information. The proposed framework comprises multiple phases that include image contrast enhancement, segmentation, feature extraction, followed by an employment of these features for training and testing of a selected classifier. Image preprocessing and feature selection being the primary steps-playing their vital role in achieving improved classification accuracy. We have empirically tested the efficacy of our technique by utilizing the well-known Lungs Image Consortium Database dataset. The results prove that the technique is highly effective for reducing FPRs with an impressive sensitivity rate of 97.45%.
This article was published in the following journal.
Name: Microscopy research and technique
As a non-invasive imaging modality, optical coherence tomography (OCT) can provide micrometer-resolution 3D images of retinal structures. These images can help reveal disease-related alterations below...
Automatic lung nodule detection has great significance for treating lung cancer and increasing patient survival. This work summarizes a critical review of recent techniques for automatic lung nodule d...
The aim of this study was to investigate the quantitative and qualitative effects of virtual monoenergetic images (VMI) by spectral detector computed tomography (SDCT) on calcium blooming in coronary ...
Preoperative detection of bone invasion is important in cases of gingival cancer. The aim of this study was to compare the diagnostic value of 3 imaging methods for the detection of bone invasion in u...
There is in creasing interest in computed tomography (CT) image estimations from magnetic resonance (MR) images. The estimated CT images can be utilised for attenuation correction, patient positioning...
Lung cancer is one of the leading cause of cancer related death in China. Lung cancer screening with low-dose computed tomography was considered as a better approach than radiography. Howe...
This is a longitudinal study of the long-term health impact of cannabis smoking on the lungs. Participants will be followed over a period of 10 years, and impacts of cannabis smoking on th...
In the coming years, an increase in lung nodule resection is expected, particularly in Video-assisted thoracoscopic surgery (VATS). In some situations, it is necessary to use a device for ...
To compare the diagnostic performance and time efficiency of Computer-Aided Detection (CAD) assisted reading for the identification of pulmonary nodules in chest Computed Tomography (CT) f...
The purpose of this study is to see if researchers can improve the detection of lung cancer by using a new method which will help us to take multiple snapshot images of the lungs while the...
An imaging technique using a device which combines TOMOGRAPHY, EMISSION-COMPUTED, SINGLE-PHOTON and TOMOGRAPHY, X-RAY COMPUTED in the same session.
A non-invasive method that uses a CT scanner for capturing images of blood vessels and tissues. A CONTRAST MATERIAL is injected, which helps produce detailed images that aid in diagnosing VASCULAR DISEASES.
Computed tomography where there is continuous X-ray exposure to the patient while being transported in a spiral or helical pattern through the beam of irradiation. This provides improved three-dimensional contrast and spatial resolution compared to conventional computed tomography, where data is obtained and computed from individual sequential exposures.
A method of computed tomography that uses radionuclides which emit a single photon of a given energy. The camera is rotated 180 or 360 degrees around the patient to capture images at multiple positions along the arc. The computer is then used to reconstruct the transaxial, sagittal, and coronal images from the 3-dimensional distribution of radionuclides in the organ. The advantages of SPECT are that it can be used to observe biochemical and physiological processes as well as size and volume of the organ. The disadvantage is that, unlike positron-emission tomography where the positron-electron annihilation results in the emission of 2 photons at 180 degrees from each other, SPECT requires physical collimation to line up the photons, which results in the loss of many available photons and hence degrades the image.
Computed tomography modalities which use a cone or pyramid-shaped beam of radiation.
Radiology is the branch of medicine that studies imaging of the body; X-ray (basic, angiography, barium swallows), ultrasound, MRI, CT and PET. These imaging techniques can be used to diagnose, but also to treat a range of conditions, by allowing visuali...
Cancer is not just one disease but many diseases. There are more than 100 different types of cancer. Most cancers are named for the organ or type of cell in which they start - for example, cancer that begins in the colon is called colon cancer; cancer th...
Pulmonary relating to or associated with the lungs eg Asthma, chronic bronchitis, emphysema, COPD, Cystic Fibrosis, Influenza, Lung Cancer, Pneumonia, Pulmonary Arterial Hypertension, Sleep Disorders etc Follow and track Lung Cancer News ...