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 …

Comprehensive Review on MRI-Based Brain Tumor Segmentation: A Comparative Study from 2017 Onwards

A Verma, SN Shivhare, SP Singh, N Kumar… - … Methods in Engineering, 2024 - Springer
Brain tumor segmentation has been a challenging and popular research problem in the area
of medical imaging and computer-aided diagnosis. In the last few years, especially since …

Zero-watermarking for medical images based on regions of interest detection using K-means clustering and discrete fourier transform

RE Arevalo-Ancona… - International Journal of …, 2023 - search.proquest.com
Watermarking schemes ensure digital image security and copyright protection to prevent
unauthorized distribution. Zero-watermarking methods do not modify the image. This …

Advancing image segmentation with DBO-Otsu: Addressing rubber tree diseases through enhanced threshold techniques

Z Xie, J Wu, W Tang, Y Liu - Plos one, 2024 - journals.plos.org
Addressing the profound impact of Tapping Panel Dryness (TPD) on yield and quality in the
global rubber industry, this study introduces a cutting-edge Otsu threshold segmentation …

Heart Disease Clustering Modeling Using a Combination of the K-Means Clustering Algorithm and the Elbow Method

J Wala, H Herman, R Umar… - Scientific Journal of …, 2024 - 103.23.102.168
Purpose: Heart disease is the leading cause of death throughout the world, especially in
developing countries like Indonesia. Modern approaches for diagnosing and managing …

A novel residual fourier convolution model for brain tumor segmentation of mr images

H Zhu, H He - Pattern Analysis and Applications, 2024 - Springer
Magnetic resonance imaging is an essential tool for the early diagnosis of brain tumors.
However, it is challenging for the segmentation of the brain tumor of magnetic resonance …

Robust brain tumor detection and classification via multi-technique image analysis

N Salma, GR Madhuri, B Jagadale… - Physica Scripta, 2024 - iopscience.iop.org
Accurate detection and classification of brain tumors play a critical role in neurological
diagnosis and treatment. This study presents an integrated methodology to precisely identify …

A Review of Brain Tumor Segmentation Using MRIs from 2019 to 2023 (Statistical Information, Key Achievements, and Limitations)

Y Zakeri, B Karasfi, A Jalalian - Journal of Medical and Biological …, 2024 - Springer
Purpose A brain tumor is defined as any group of atypical cells occupying space in the brain.
There are more than 120 types of them. MRI scans are used for brain tumor diagnosis since …

Al-enabled properties distribution prediction for high-pressure die casting Al-Si alloy

YT Yang, ZY Qiu, Z Zheng, LX Pu, DD Chen… - Advances in …, 2024 - Springer
High-pressure die casting (HPDC) is one of the most popular mass production processes in
the automotive industry owing to its capability for part consolidation. However, the …

Lesion Classification of Coronary Artery CTA Images Based on CBAM and Transfer Learning

Y Jin, X Ye, N Feng, Z Wang, X Hei… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Classification of coronary artery stenosis is essential in assisting physicians in diagnosing
cardiovascular diseases. However, due to the complexity of medical diagnosis and the …