AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 6101 to 6110 of 10288 articles

Key factors in a rigorous longitudinal image-based assessment of retinopathy of prematurity.

Scientific reports
To describe a database of longitudinally graded telemedicine retinal images to be used as a comparator for future studies assessing grader recall bias and ability to detect typical progression (e.g. International Classification of Retinopathy of Prem...

Image-level supervised segmentation for human organs with confidence cues.

Physics in medicine and biology
Image segmentation for human organs is an important task for the diagnosis and treatment of diseases. Current deep learning-based methods are fully supervised and need pixel-level labels. Since the medical images are highly specialized and complex, t...

Assessment of an Artificial Intelligence Algorithm for Detection of Intracranial Hemorrhage.

World neurosurgery
BACKGROUND: Immediate and accurate detection of intracranial hemorrhages (ICHs) is essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has the potential to provide this, but the assessment of these methods need...

Deep learning approaches for automated classification and segmentation of head and neck cancers and brain tumors in magnetic resonance images: a meta-analysis study.

International journal of computer assisted radiology and surgery
PURPOSE: Deep learning (DL) has led to widespread changes in automated segmentation and classification for medical purposes. This study is an attempt to use statistical methods to analyze studies related to segmentation and classification of head and...

Automatic liver segmentation using 3D convolutional neural networks with a hybrid loss function.

Medical physics
PURPOSE: Automatic liver segmentation from abdominal computed tomography (CT) images is a fundamental task in computer-assisted liver surgery programs. Many liver segmentation algorithms are very sensitive to fuzzy boundaries and heterogeneous pathol...

Effects of Image Degradation and Degradation Removal to CNN-Based Image Classification.

IEEE transactions on pattern analysis and machine intelligence
Just like many other topics in computer vision, image classification has achieved significant progress recently by using deep learning neural networks, especially the Convolutional Neural Networks (CNNs). Most of the existing works focused on classif...

Appearance and Pose-Conditioned Human Image Generation Using Deformable GANs.

IEEE transactions on pattern analysis and machine intelligence
In this paper, we address the problem of generating person images conditioned on both pose and appearance information. Specifically, given an image x of a person and a target pose P(x), extracted from an image x, we synthesize a new image of that per...

Machine learning-based classification of mitochondrial morphology in primary neurons and brain.

Scientific reports
The mitochondrial network continually undergoes events of fission and fusion. Under physiologic conditions, the network is in equilibrium and is characterized by the presence of both elongated and punctate mitochondria. However, this balanced, homeos...

Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features.

Physics in medicine and biology
OBJECTIVES: This study aims to develop a computer-aided diagnosis (CADx) scheme to classify between benign and malignant ground glass nodules (GGNs), and fuse deep leaning and radiomics imaging features to improve the classification performance.

Automatic attenuation map estimation from SPECT data only for brain perfusion scans using convolutional neural networks.

Physics in medicine and biology
In clinical brain SPECT, correction for photon attenuation in the patient is essential to obtain images which provide quantitative information on the regional activity concentration per unit volume (kBq.[Formula: see text]). This correction generally...