Medical image identification methods: A review
J Li, P Jiang, Q An, GG Wang, HF Kong - Computers in Biology and …, 2024 - Elsevier
The identification of medical images is an essential task in computer-aided diagnosis,
medical image retrieval and mining. Medical image data mainly include electronic health …
medical image retrieval and mining. Medical image data mainly include electronic health …
Efficient artificial intelligence approaches for medical image processing in healthcare: comprehensive review, taxonomy, and analysis
OAMF Alnaggar, BN Jagadale, MAN Saif… - Artificial Intelligence …, 2024 - Springer
In healthcare, medical practitioners employ various imaging techniques such as CT, X-ray,
PET, and MRI to diagnose patients, emphasizing the crucial need for early disease detection …
PET, and MRI to diagnose patients, emphasizing the crucial need for early disease detection …
A Machine Learning Model for Content-Based Image Retrieval
B Singh, EK Kaur, C Choudhary - 2023 2nd International …, 2023 - ieeexplore.ieee.org
With advancement in the modern era, digital data is the new asset. Now making large image
datasets is not that laborious task with improvement in image collection and data storage …
datasets is not that laborious task with improvement in image collection and data storage …
Content-based image retrieval using handcraft feature fusion in semantic pyramid
The main challenge of image retrieval systems is to retrieve similar samples in a way that
can be interpreted in a semantic relationship with the user's query image. In recent years …
can be interpreted in a semantic relationship with the user's query image. In recent years …
Image retrieval algorithm based on locality-sensitive hash using convolutional neural network and attention mechanism
Y Luo, W Li, X Ma, K Zhang - Information, 2022 - mdpi.com
With the continuous progress of image retrieval technology, in the field of image retrieval, the
speed of a search for a desired image from a great deal of image data becomes a hot issue …
speed of a search for a desired image from a great deal of image data becomes a hot issue …
Content-based image retrieval through fusion of deep features extracted from segmented neutrosophic using depth map
The main challenge of content-based image retrieval systems is the difference between how
images are described using algorithms and how humans understand the semantic concepts …
images are described using algorithms and how humans understand the semantic concepts …
Triplet Learning for Chest X-Ray Image Search in Automated COVID-19 Analysis
Chest radiology images such as CT scans and X-ray images have been extensively
employed in computer-assisted analysis of COVID-19, utilizing various learning-based …
employed in computer-assisted analysis of COVID-19, utilizing various learning-based …
Echoes of images: multi-loss network for image retrieval in vision transformers
This paper introduces a novel approach to enhance content-based image retrieval,
validated on two benchmark datasets: ISIC-2017 and ISIC-2018. These datasets comprise …
validated on two benchmark datasets: ISIC-2017 and ISIC-2018. These datasets comprise …
Content-based image retrieval using DNA transcription and translation
DNA carries the genetic information of almost all the living beings on the earth. The flow of
genetic information takes place by a series of transcription and translation reactions in which …
genetic information takes place by a series of transcription and translation reactions in which …
Variational autoencoders for medical image retrieval
C Alves, AJM Traina - … on innovations in intelligent systems and …, 2022 - ieeexplore.ieee.org
This paper presents an approach based on Variational Autoencoders (VAEs) for
unsupervised learning of deep features for Content-Based Medical Image Retrieval …
unsupervised learning of deep features for Content-Based Medical Image Retrieval …