U-mamba: Enhancing long-range dependency for biomedical image segmentation
Convolutional Neural Networks (CNNs) and Transformers have been the most popular
architectures for biomedical image segmentation, but both of them have limited ability to …
architectures for biomedical image segmentation, but both of them have limited ability to …
One model to rule them all: Towards universal segmentation for medical images with text prompts
In this study, we focus on building up a model that can Segment Anything in medical
scenarios, driven by Text prompts, termed as SAT. Our main contributions are three folds:(i) …
scenarios, driven by Text prompts, termed as SAT. Our main contributions are three folds:(i) …
Unleashing the potential of SAM for medical adaptation via hierarchical decoding
Abstract The Segment Anything Model (SAM) has garnered significant attention for its
versatile segmentation abilities and intuitive prompt-based interface. However its application …
versatile segmentation abilities and intuitive prompt-based interface. However its application …
[HTML][HTML] Pancreatic Ductal Adenocarcinoma (PDAC): A Review of Recent Advancements Enabled by Artificial Intelligence
A Mukund, MA Afridi, A Karolak, MA Park, JB Permuth… - Cancers, 2024 - mdpi.com
Simple Summary Pancreatic Ductal Adenocarcinoma (PDAC) remains one of the deadliest
forms of cancer, characterized by high rates of metastasis, late detection, and poor …
forms of cancer, characterized by high rates of metastasis, late detection, and poor …
[HTML][HTML] Artificial Intelligence in Pancreatic Image Analysis: A Review
W Liu, B Zhang, T Liu, J Jiang, Y Liu - Sensors, 2024 - mdpi.com
Pancreatic cancer is a highly lethal disease with a poor prognosis. Its early diagnosis and
accurate treatment mainly rely on medical imaging, so accurate medical image analysis is …
accurate treatment mainly rely on medical imaging, so accurate medical image analysis is …
3D-TransUNet for Brain Metastases Segmentation in the BraTS2023 Challenge
Segmenting brain tumors is complex due to their diverse appearances and scales. Brain
metastases, the most common type of brain tumor, are a frequent complication of cancer …
metastases, the most common type of brain tumor, are a frequent complication of cancer …
Multi-scale Knowledge Transfer Vision Transformer for 3D vessel shape segmentation
MJ Hua, J Wu, Z Zhong - Computers & Graphics, 2024 - Elsevier
In order to facilitate the robust and precise 3D vessel shape extraction and quantification
from in-vivo Magnetic Resonance Imaging (MRI), this paper presents a novel multi-scale …
from in-vivo Magnetic Resonance Imaging (MRI), this paper presents a novel multi-scale …
Multi-task Learning for Motion Analysis and Segmentation in 3D Echocardiography
Characterizing left ventricular deformation and strain using 3D+ time echocardiography
provides useful insights into cardiac function and can be used to detect and localize …
provides useful insights into cardiac function and can be used to detect and localize …
2.5 D UNet with context-aware feature sequence fusion for accurate esophageal tumor semantic segmentation
K Xu, F Zhang, Y Huang, X Huang - Physics in Medicine & …, 2024 - iopscience.iop.org
Segmenting esophageal tumor from computed tomography (CT) sequence images can
assist doctors in diagnosing and treating patients with this malignancy. However, accurately …
assist doctors in diagnosing and treating patients with this malignancy. However, accurately …
Large Language Model-Augmented Auto-Delineation of Treatment Target Volume in Radiation Therapy
P Rajendran, Y Yang, TR Niedermayr… - arXiv preprint arXiv …, 2024 - arxiv.org
Radiation therapy (RT) is one of the most effective treatments for cancer, and its success
relies on the accurate delineation of targets. However, target delineation is a comprehensive …
relies on the accurate delineation of targets. However, target delineation is a comprehensive …