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Medical image diagnosis based on adaptive Hybrid Quantum CNN
Hybrid quantum systems have shown promise in image classification by combining the strengths of both classical and quantum algorithms. These systems...
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Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization
The early detection and accurate diagnosis of liver fibrosis, a progressive and potentially serious liver condition, are crucial for effective...
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A hybrid deep CNN model for brain tumor image multi-classification
The current approach to diagnosing and classifying brain tumors relies on the histological evaluation of biopsy samples, which is invasive,...
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HCformer: Hybrid CNN-Transformer for LDCT Image Denoising
Low-dose computed tomography (LDCT) is an effective way to reduce radiation exposure for patients. However, it will increase the noise of...
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Classification of benign and malignant subtypes of breast cancer histopathology imaging using hybrid CNN-LSTM based transfer learning
BackgroundGrading of cancer histopathology slides requires more pathologists and expert clinicians as well as it is time consuming to look manually...
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Artificial Humming Bird Optimization–Based Hybrid CNN-RNN for Accurate Exudate Classification from Fundus Images
Diabetic retinopathy is the predominant cause of visual impairment in diabetes patients. The early detection process can prevent diabetes patients...
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Deep CNN with Hybrid Binary Local Search and Particle Swarm Optimizer for Exudates Classification from Fundus Images
Diabetic retinopathy is a chronic condition that causes vision loss if not detected early. In the early stage, it can be diagnosed with the aid of...
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Hybrid architecture based intelligent diagnosis assistant for GP
As the first point of contact for patients, General Practitioners (GPs) play a crucial role in the National Health Service (NHS). An accurate primary...
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CNN-Res: deep learning framework for segmentation of acute ischemic stroke lesions on multimodal MRI images
BackgroundAccurate segmentation of stroke lesions on MRI images is very important for neurologists in the planning of post-stroke care. Segmentation...
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Cervical Cancer Detection Using Hybrid Pooling-Based Convolutional Neural Network Approach
The most prevalent deadly occurring disease nowadays in women is nothing but cervical cancer which has to be avoided by frequently having screenings...
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A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure
IntroductionEpilepsy is a disease characterized by an excessive discharge in neurons generally provoked without any external stimulus, known as...
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A Deep Learning-Based Approach for Cervical Cancer Classification Using 3D CNN and Vision Transformer
Cervical cancer is a significant health problem worldwide, and early detection and treatment are critical to improving patient outcomes. To address...
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Optimal Deep CNN–Based Vectorial Variation Filter for Medical Image Denoising
Medical imaging has acquired more attention due to the emerging design of wireless technologies, the internet, and data storage. The reflection of...
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Spatial and geometric learning for classification of breast tumors from multi-center ultrasound images: a hybrid learning approach
BackgroundBreast cancer is the most common cancer among women, and ultrasound is a usual tool for early screening. Nowadays, deep learning technique...
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A 3D reconstruction method based on multi-views of contours segmented with CNN-transformer for long bones
PurposeIn computer-assisted diagnosis for orthopedic treatment, 3D reconstruction of bones is critical. Traditional 3D imaging technologies like CT...
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Polyp Segmentation Using a Hybrid Vision Transformer and a Hybrid Loss Function
Accurate and early detection of precursor adenomatous polyps and their removal at the early stage can significantly decrease the mortality rate and...
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Identification of difficult laryngoscopy using an optimized hybrid architecture
BackgroundIdentification of difficult laryngoscopy is a frequent demand in cervical spondylosis clinical surgery. This work aims to develop a hybrid...
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An automated detection of epileptic seizures EEG using CNN classifier based on feature fusion with high accuracy
BackgroundEpilepsy is a neurological disorder that is usually detected by electroencephalogram (EEG) signals. Since manual examination of epilepsy...
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A hierarchical GAN method with ensemble CNN for accurate nodule detection
PurposeLung cancer can evolve into one of the deadliest diseases whose early detection is one of the major survival factors. However, early detection...
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Hybrid Convolution Neural Network in Classification of Cancer in Histopathology Images
Cancer statistics in 2020 reveals that breast cancer is the most common form of cancer among women in India. One in 28 women is likely to develop...
