Intelligence in the Internet of Medical Things era: A systematic review of current and future trends
Abstract Internet of Medical Things (IoMT) envisions a network of medical devices and
people, which use wireless communication to enable the exchange of healthcare data …
people, which use wireless communication to enable the exchange of healthcare data …
A survey of methods for brain tumor segmentation-based MRI images
YMA Mohammed, S El Garouani… - … of Computational Design …, 2023 - academic.oup.com
Brain imaging techniques play an important role in determining the causes of brain cell
injury. Therefore, earlier diagnosis of these diseases can be led to give rise to bring huge …
injury. Therefore, earlier diagnosis of these diseases can be led to give rise to bring huge …
A brain tumor identification and classification using deep learning based on CNN-LSTM method
R Vankdothu, MA Hameed, H Fatima - Computers and Electrical …, 2022 - Elsevier
Brain tumors are one of the most often diagnosed malignant tumors in persons of all ages.
Recognizing its grade is challenging for radiologists in health monitoring and automated …
Recognizing its grade is challenging for radiologists in health monitoring and automated …
Rice yield estimation based on K-means clustering with graph-cut segmentation using low-altitude UAV images
Predicting the harvest yield enables farm practices to be modified throughout the growing
season, with potential to increase the final yield. Unmanned aerial vehicle (UAV) based …
season, with potential to increase the final yield. Unmanned aerial vehicle (UAV) based …
Detection and classification of cancer from microscopic biopsy images using clinically significant and biologically interpretable features
A framework for automated detection and classification of cancer from microscopic biopsy
images using clinically significant and biologically interpretable features is proposed and …
images using clinically significant and biologically interpretable features is proposed and …
Multiscale feature-clustering-based fully convolutional autoencoder for fast accurate visual inspection of texture surface defects
Visual inspection of texture surface defects is still a challenging task in the industrial
automation field due to the tremendous changes in the appearance of various surface …
automation field due to the tremendous changes in the appearance of various surface …
Explainable artificial intelligence-based edge fuzzy images for COVID-19 detection and identification
Q Hu, FNB Gois, R Costa, L Zhang, L Yin… - Applied Soft …, 2022 - Elsevier
The COVID-19 pandemic continues to wreak havoc on the world's population's health and
well-being. Successful screening of infected patients is a critical step in the fight against it …
well-being. Successful screening of infected patients is a critical step in the fight against it …
A survey on brain tumor detection using image processing techniques
L Kapoor, S Thakur - … on cloud computing, data science & …, 2017 - ieeexplore.ieee.org
Biomedical Image Processing is a growing and demanding field. It comprises of many
different types of imaging methods likes CT scans, X-Ray and MRI. These techniques allow …
different types of imaging methods likes CT scans, X-Ray and MRI. These techniques allow …
Detection and classification of brain tumours from MRI images using faster R-CNN
K Salçin - Tehnički glasnik, 2019 - hrcak.srce.hr
Sažetak Magnetic resonance imaging (MRI) is a useful method for diagnosis of tumours in
human brain. In this work, MRI images have been analysed to detect the regions containing …
human brain. In this work, MRI images have been analysed to detect the regions containing …
Exploring the u-net++ model for automatic brain tumor segmentation
The accessibility and potential of deep learning techniques have increased considerably
over the past years. Image segmentation is one of the many fields which have seen novel …
over the past years. Image segmentation is one of the many fields which have seen novel …