Deep Convolutional Spiking Neural Network optimized with Arithmetic optimization algorithm for lung disease detection using chest X-ray images

R Rajagopal, R Karthick, P Meenalochini… - … Signal Processing and …, 2023 - Elsevier
Lung disease is a most common disease all over the world. A numerous feature extraction
with classification models were discussed previously about the lung disease, but those …

MRFE-CNN: Multi-route feature extraction model for breast tumor segmentation in Mammograms using a convolutional neural network

R Ranjbarzadeh, N Tataei Sarshar… - Annals of Operations …, 2023 - Springer
Breast cancer is cancer that develops from the breast tissue and has been recognized as
one of the most dangerous and deadly diseases that is the second leading cause of cancer …

Convolutional neural network: an overview and application in image classification

S Tripathy, R Singh - Proceedings of Third International Conference on …, 2022 - Springer
As the field of artificial intelligence keeps progressing each year, it is noticeable how deep
learning is becoming a significant approach for information processing like image …

An extended approach to the diagnosis of tumour location in breast cancer using deep learning

S Jafarzadeh Ghoushchi, R Ranjbarzadeh… - Journal of Ambient …, 2023 - Springer
Breast cancer is one of the most common and deadly cancers in women. However, early
detection increases the likelihood of survival by 100%. Radiologists use mammograms to …

[HTML][HTML] Parameter selection for CLAHE using multi-objective cuckoo search algorithm for image contrast enhancement

U Kuran, EC Kuran - Intelligent Systems with Applications, 2021 - Elsevier
Contrast enhancement techniques that are proposed in the literature are devised to
enhance image quality so as to provide better details for different image processing tasks …

Automation of brain tumor identification using efficientnet on magnetic resonance images

S Tripathy, R Singh, M Ray - Procedia Computer Science, 2023 - Elsevier
The general method for classification of brain tumors is through biopsy, but biopsy is
performed only after a surgery where a small tissue is removed from the brain and examined …

Detection of cotton leaf disease using image processing techniques

S Tripathy - Journal of Physics: Conference Series, 2021 - iopscience.iop.org
In the area of research, diagnosis of disease symptoms in the plants duly applying image
processing methods is a matter of big concern. The need of the hour is to prepare an …

[PDF][PDF] An Efficient Breast Cancer Detection Framework for Medical Diagnosis Applications.

NF Soliman, NS Ali, MI Aly, AD Algarni… - … , Materials & Continua, 2022 - researchgate.net
Breast cancer is the most common type of cancer, and it is the reason for cancer death toll in
women in recent years. Early diagnosis is essential to handle breast cancer patients for …

BRMI-Net: Deep Learning Features and Flower Pollination-Controlled Regula Falsi-Based Feature Selection Framework for Breast Cancer Recognition in …

S Rehman, MA Khan, A Masood, NA Almujally, J Baili… - Diagnostics, 2023 - mdpi.com
The early detection of breast cancer using mammogram images is critical for lowering
women's mortality rates and allowing for proper treatment. Deep learning techniques are …

Breast cancer segmentation in mammogram using artificial intelligence and image processing: a systematic review

W Ansar, B Raza - Current Chinese Science, 2023 - ingentaconnect.com
Background: Breast cancer is the second leading cause of death in females worldwide.
Mammograms are useful in early cancer diagnosis as well when the patient can sense …