Improved UNet with attention for medical image segmentation
Medical image segmentation is crucial for medical image processing and the development
of computer-aided diagnostics. In recent years, deep Convolutional Neural Networks …
of computer-aided diagnostics. In recent years, deep Convolutional Neural Networks …
Brain tumor classification and detection using hybrid deep tumor network
GA Amran, MS Alsharam, AOA Blajam, AA Hasan… - Electronics, 2022 - mdpi.com
Brain tumor (BTs) is considered one of the deadly, destructive, and belligerent disease, that
shortens the average life span of patients. Patients with misdiagnosed and insufficient …
shortens the average life span of patients. Patients with misdiagnosed and insufficient …
Lung cancer classification using modified U-Net based lobe segmentation and nodule detection
Lung cancer is the most common cause of cancer deaths worldwide. Early detection is
crucial for successful treatment and increasing patient survival rates. Artificial intelligence …
crucial for successful treatment and increasing patient survival rates. Artificial intelligence …
Implementation of a modified U-Net for medical image segmentation on edge devices
Deep learning techniques, particularly convolutional neural networks, have shown great
potential in computer vision and medical imaging applications. However, deep learning …
potential in computer vision and medical imaging applications. However, deep learning …
UcUNet: A lightweight and precise medical image segmentation network based on efficient large kernel U-shaped convolutional module design
S Yang, X Zhang, Y Chen, Y Jiang, Q Feng, L Pu… - Knowledge-Based …, 2023 - Elsevier
In recent years, precise medical image segmentation methods based on the encoder–
decoder structure have attracted much attention, but there are still some limitations. They …
decoder structure have attracted much attention, but there are still some limitations. They …
Multi-scale context UNet-like network with redesigned skip connections for medical image segmentation
L Qian, C Wen, Y Li, Z Hu, X Zhou, X ** Review
Background: Transformer-based models are gaining popularity in medical imaging and
cancer imaging applications. Many recent studies have demonstrated the use of transformer …
cancer imaging applications. Many recent studies have demonstrated the use of transformer …
NDNN based U-Net: An innovative 3D brain tumor segmentation method
Identifying and segmenting brain tumors using multi-sequence 3D volumetric MRI scans is
time-consuming and challenging. Deep learning-based automatic image segmentation …
time-consuming and challenging. Deep learning-based automatic image segmentation …
ResMIBCU-Net: an encoder–decoder network with residual blocks, modified inverted residual block, and bi-directional ConvLSTM for impacted tooth segmentation in …
Objective Impacted tooth is a common problem that can occur at any age, causing tooth
decay, root resorption, and pain in the later stages. In recent years, major advances have …
decay, root resorption, and pain in the later stages. In recent years, major advances have …
An automated multi-class skin lesion diagnosis by embedding local and global features of Dermoscopy images
Skin cancer is an increasing cause of concern among cancers worldwide. There has been
extensive research carried out all over the globe for the early detection of skin cancer to …
extensive research carried out all over the globe for the early detection of skin cancer to …