AIMC Topic: Image Processing, Computer-Assisted

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RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model.

Sensors (Basel, Switzerland)
Cervical cancer is one of the main causes of death from cancer in women. However, it can be treated successfully at an early stage. This study aims to propose an image processing algorithm based on acetowhite, which is an important criterion for diag...

Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images.

Scientific reports
An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed on a cone-beam computed tomography (CBCT) dataset....

End-to-End Residual Network for Light Field Reconstruction on Raw Images and View Image Stacks.

Sensors (Basel, Switzerland)
Light field (LF) technology has become a focus of great interest (due to its use in many applications), especially since the introduction of the consumer LF camera, which facilitated the acquisition of dense LF images. Obtaining densely sampled LF im...

Detecting and Extracting Brain Hemorrhages from CT Images Using Generative Convolutional Imaging Scheme.

Computational intelligence and neuroscience
PURPOSE: The need for computerized medical assistance for accurate detection of brain hemorrhage from Computer Tomography (CT) images is more mandatory than conventional clinical tests. Recent technologies and advanced computerized algorithms follow ...

Recent advancement in cancer diagnosis using machine learning and deep learning techniques: A comprehensive review.

Computers in biology and medicine
Being a second most cause of mortality worldwide, cancer has been identified as a perilous disease for human beings, where advance stage diagnosis may not help much in safeguarding patients from mortality. Thus, efforts to provide a sustainable archi...

Pulmonary emphysema quantification at low dose chest CT using Deep Learning image reconstruction.

European journal of radiology
PURPOSE: Quantitative analysis of emphysema volume is affected by the radiation dose and the CT reconstruction technique. We aim to evaluate the influence of a commercially available deep learning image reconstruction algorithm (DLIR) on the quantifi...

Deep Learning for Person Re-Identification: A Survey and Outlook.

IEEE transactions on pattern analysis and machine intelligence
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increa...

A Novel Framework With Weighted Decision Map Based on Convolutional Neural Network for Cardiac MR Segmentation.

IEEE journal of biomedical and health informatics
For diagnosing cardiovascular disease, an accurate segmentation method is needed. There are several unresolved issues in the complex field of cardiac magnetic resonance imaging, some of which have been partially addressed by using deep neural network...

Detecting Buildings and Nonbuildings from Satellite Images Using U-Net.

Computational intelligence and neuroscience
Automatic building detection from high-resolution satellite imaging images has many applications. Understanding socioeconomic development and keeping track of population migrations are essential for effective civic planning. These civil feature syste...

Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: The GE Discovery NM (DNM) 530c/570c are dedicated cardiac SPECT scanners with 19 detector modules designed for stationary imaging. This study aims to incorporate additional projection angular sampling to improve reconstruction quality. A ...