Descriptive analysis of dental X-ray images using various practical methods: A review
A Kumar, HS Bhadauria, A Singh - PeerJ Computer Science, 2021 - peerj.com
In dentistry, practitioners interpret various dental X-ray imaging modalities to identify tooth-
related problems, abnormalities, or teeth structure changes. Another aspect of dental …
related problems, abnormalities, or teeth structure changes. Another aspect of dental …
Analysis of quantum noise-reducing filters on chest X-ray images: A review
TB Chandra, K Verma - Measurement, 2020 - Elsevier
Radiography is one of the important clinical adjuncts for preliminary disease investigation.
The X-ray images are corrupted with inherent quantum noise affecting the performance of …
The X-ray images are corrupted with inherent quantum noise affecting the performance of …
Image denoising in the deep learning era
S Izadi, D Sutton, G Hamarneh - Artificial Intelligence Review, 2023 - Springer
Over the last decade, the number of digital images captured per day has increased
exponentially, due to the accessibility of imaging devices. The visual quality of photographs …
exponentially, due to the accessibility of imaging devices. The visual quality of photographs …
Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images
Chest X-ray images are used in deep convolutional neural networks for the detection of
COVID-19, the greatest human challenge of the 21st century. Robustness to noise and …
COVID-19, the greatest human challenge of the 21st century. Robustness to noise and …
An image segmentation approach based on fuzzy c-means and dynamic particle swarm optimization algorithm
N Dhanachandra, YJ Chanu - Multimedia tools and applications, 2020 - Springer
Image segmentation has considered an important step in image processing. Fuzzy c-means
(FCM) is one of the commonly used clustering algorithms because of its simplicity and …
(FCM) is one of the commonly used clustering algorithms because of its simplicity and …
Kidney tumor semantic segmentation using deep learning: A survey of state-of-the-art
A Abdelrahman, S Viriri - Journal of imaging, 2022 - mdpi.com
Cure rates for kidney cancer vary according to stage and grade; hence, accurate diagnostic
procedures for early detection and diagnosis are crucial. Some difficulties with manual …
procedures for early detection and diagnosis are crucial. Some difficulties with manual …
A novel complex-valued convolutional neural network for medical image denoising
Several applications of complex-valued networks have been reported for computer vision
tasks like image processing and classification. However, complex-valued convolutional …
tasks like image processing and classification. However, complex-valued convolutional …
Automatic detection of COVID-19 infection from chest X-ray using deep learning
ABSTRACT COVID-19 infection has created a panic across the globe in recent times. Early
detection of COVID-19 infection can save many lives in the prevailing situation. This virus …
detection of COVID-19 infection can save many lives in the prevailing situation. This virus …
This looks like that... does it? shortcomings of latent space prototype interpretability in deep networks
Deep neural networks that yield human interpretable decisions by architectural design have
lately become an increasingly popular alternative to post hoc interpretation of traditional …
lately become an increasingly popular alternative to post hoc interpretation of traditional …
A comparative analysis of image denoising problem: noise models, denoising filters and applications
Noise reduction is a perplexing undertaking for the researchers in digital image processing
and has a wide range of applications in automation, IoT (Internet of Things), medicine, etc …
and has a wide range of applications in automation, IoT (Internet of Things), medicine, etc …