5 citations · 9 across the 5 of their papers we have counts for
5 papers
MambaU-Lite: A Lightweight Model based on Mamba and Integrated Channel-Spatial Attention for Skin Lesion Segmentation
Thi-Nhu-Quynh Nguyen, Quang-Huy Ho, Duy-Thai Nguyen +3
Early detection of skin abnormalities plays a crucial role in diagnosing and treating skin cancer. Segmentation of affected skin regions using AI-powered devices is relatively comm…
Trans2Unet: Neural fusion for Nuclei Semantic Segmentation
Dinh-Phu Tran, Quoc-Anh Nguyen, Van-Truong Pham +1
Nuclei segmentation, despite its fundamental role in histopathological image analysis, is still a challenge work. The main challenge of this task is the existence of overlapping ar…
AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentation
Viet-Thanh Nguyen, Van-Truong Pham, Thi-Thao Tran
Skin lesion segmentation is a critical task in computer-aided diagnosis systems for dermatological diseases. Accurate segmentation of skin lesions from medical images is essential…
LiteNeXt: A Novel Lightweight ConvMixer-based Model with Self-embedding Representation Parallel for Medical Image Segmentation
Ngoc-Du Tran, Thi-Thao Tran, Quang-Huy Nguyen +2
The emergence of deep learning techniques has advanced the image segmentation task, especially for medical images. Many neural network models have been introduced in the last decad…
1M parameters are enough? A lightweight CNN-based model for medical image segmentation
Binh-Duong Dinh, Thanh-Thu Nguyen, Thi-Thao Tran +1
Convolutional neural networks (CNNs) and Transformer-based models are being widely applied in medical image segmentation thanks to their ability to extract high-level features and…