[HTML][HTML] A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce
Every nation's economic development depends heavily on agriculture. Fulfilling the current
population's need for food is becoming increasingly difficult because of factors including …
population's need for food is becoming increasingly difficult because of factors including …
Survey on deep learning in multimodal medical imaging for cancer detection
The task of multimodal cancer detection is to determine the locations and categories of
lesions by using different imaging techniques, which is one of the key research methods for …
lesions by using different imaging techniques, which is one of the key research methods for …
Skin cancer classification based on an optimized convolutional neural network and multicriteria decision-making
Skin cancer is a type of cancer disease in which abnormal alterations in skin characteristics
can be detected. It can be treated if it is detected early. Many artificial intelligence-based …
can be detected. It can be treated if it is detected early. Many artificial intelligence-based …
HT-RCM: Hashimoto's Thyroiditis Ultrasound Image Classification Model Based on Res-FCT and Res-CAM
W Jiang, K Chen, Z Liang, T Luo, G Yue… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
The early lesions of Hashimoto's thyroiditis are inconspicuous, and the ultrasonic features of
these early lesions are indistinguishable from other thyroid diseases. This paper proposes a …
these early lesions are indistinguishable from other thyroid diseases. This paper proposes a …
Kidney Tumor Classification on CT images using Self-supervised Learning
One of the most common diseases affecting society around the world is kidney tumor. The
risk of kidney disease increases due to reasons such as consumption of ready-made food …
risk of kidney disease increases due to reasons such as consumption of ready-made food …
Spatio-temporal collaborative multiple-stream transformer network for liver lesion classification on multiple-sequence magnetic resonance imaging
Accurate identification of focal liver lesions is essential for determining the appropriate
therapeutic approach in clinical practice. Magnetic resonance imaging (MRI) is a valuable …
therapeutic approach in clinical practice. Magnetic resonance imaging (MRI) is a valuable …
[HTML][HTML] Local interpretable model-agnostic explanation approach for medical imaging analysis: A systematic literature review
Background: The interpretability and explainability of machine learning (ML) and artificial
intelligence systems are critical for generating trust in their outcomes in fields such as …
intelligence systems are critical for generating trust in their outcomes in fields such as …
Computer-aided diagnosis of liver cancer with improved SegNet and deep stacking ensemble model
VSD Tejaswi, V Rachapudi - Computational Biology and Chemistry, 2024 - Elsevier
Liver cancer is a leading cause of cancer-related deaths, often diagnosed at advanced
stages due to reliance on traditional imaging methods. Existing computer-aided diagnosis …
stages due to reliance on traditional imaging methods. Existing computer-aided diagnosis …
A novel hybrid CNN-KNN ensemble voting classifier for Parkinson's disease prediction from hand sketching images
Parkinson's disease is a progressive neurodegenerative disorder that causes significant
physical disabilities and reduces the quality of life. This disease is caused by the loss of …
physical disabilities and reduces the quality of life. This disease is caused by the loss of …
Customized m-RCNN and hybrid deep classifier for liver cancer segmentation and classification
Diagnosing liver disease presents a significant medical challenge in impoverished
countries, with over 30 billion individuals succumbing to it each year. Existing models for …
countries, with over 30 billion individuals succumbing to it each year. Existing models for …