Results 31 to 40 of about 896 (171)
Bioengineering, 2023 The quality of breast ultrasound images has a significant impact on the accuracy of disease diagnosis. Existing image quality assessment (IQA) methods usually use pixel-level feature statistical methods or end-to-end deep learning methods, which focus on
Ziwen Wang +7 more
doaj +1 more source
Journal of Imaging, 2018 Automatic assessing the quality of an image is a critical problem for a wide range of applications in the fields of computer vision and image processing. For example, many computer vision applications, such as biometric identification, content retrieval,
Pedro Garcia Freitas +3 more
doaj +1 more source
PMT-IQA: Progressive Multi-task Learning for Blind Image Quality Assessment
, 2023 Blind image quality assessment (BIQA) remains challenging due to the diversity of distortion and image content variation, which complicate the distortion patterns crossing different scales and aggravate the difficulty of the regression problem for BIQA.
Qingyi Pan +4 more
openaire +2 more sources
Deep learning-driven multi-view multi-task image quality assessment method for chest CT image
BioMedical Engineering OnLine, 2023 Background Chest computed tomography (CT) image quality impacts radiologists’ diagnoses. Pre-diagnostic image quality assessment is essential but labor-intensive and may have human limitations (fatigue, perceptual biases, and cognitive biases).
Jialin Su +6 more
doaj +1 more source
Applied Sciences, 2023 The purpose of the no-reference image quality assessment (NR-IQA) is to measure perceived image quality based on subjective judgments; however, due to the lack of a clean reference image, this is a complicated and unresolved challenge.
Jihyoung Ryu
doaj +1 more source
TIQA-MRI: Toolbox for Perceptual Image Quality Assessment of Magnetic Resonance Images
SoftwareXMagnetic Resonance Imaging (MRI) plays a pivotal role in medical diagnostics and research as a non-invasive imaging tool. The accuracy and reliability of clinical evaluations depend heavily on the quality of MRI images, making high-quality imaging ...
Igor Stępień
doaj +1 more source
LMM-IQA: Image Quality Assessment for Low-Dose CT Imaging
CoRRLow-dose computed tomography (CT) represents a significant improvement in patient safety through lower radiation doses, but increased noise, blur, and contrast loss can diminish diagnostic quality. Therefore, consistency and robustness in image quality assessment become essential for clinical applications. In this study, we propose an LLM-based quality
Kagan Celik +3 more
openaire +2 more sources
SAM-IQA: Can Segment Anything Boost Image Quality Assessment?
CoRR, 2023 Image Quality Assessment (IQA) is a challenging task that requires training on massive datasets to achieve accurate predictions. However, due to the lack of IQA data, deep learning-based IQA methods typically rely on pre-trained networks trained on massive datasets as feature extractors to enhance their generalization ability, such as the ResNet ...
Xinpeng Li 0002 +3 more
openaire +2 more sources
End-to-End Image Patch Quality Assessment for Image/Video With Compression Artifacts
IEEE Access, 2020 In this paper, we present an experimental image quality assessment (IQA) method for image/video patches with compression artifacts. Using the High Efficiency Video Coding (HEVC) standard, we create a new database of image patches with compression ...
Tung Thanh Pham +4 more
doaj +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley +1 more source