.png){kind=icon}
返回
Multidimensional Directionality-Enhanced Segmentation via large vision model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.media.2024.103395.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Optical Coherence Tomography (OCT) facilitates a comprehensive examination of macular edema and associated lesions. Manual delineation of retinal fluid is labor-intensive and error-prone, necessitating an automated diagnostic and therapeutic planning mechanism. Conventional supervised learning models are hindered by dataset limitations, while Transformer-based large vision models exhibit challenges in medical image segmentation, particularly in detecting small, subtle lesions in OCT images. This paper introduces the Multidimensional Directionality-Enhanced Retinal Fluid Segmentation framework (MD-DERFS), which reduces the limitations inherent in conventional supervised models by adapting a transformer-based large vision model for macular edema segmentation. The proposed MD-DERFS introduces a Multi-Dimensional Feature Re-Encoder Unit (MFU) to augment the model's proficiency in recognizing specific textures and pathological features through directional prior extraction and an Edema Texture Mapping Unit (ETMU), a Cross-scale Directional Insight Network (CDIN) furnishes a holistic perspective spanning local to global details, mitigating the large vision model's deficiencies in capturing localized feature information. Additionally, the framework is augmented by a Harmonic Minutiae Segmentation Equilibrium loss (G HMSE ) that can address the challenges of data imbalance and annotation scarcity in macular edema datasets. Empirical validation on the MacuScan-8k dataset shows that MD-DERFS surpasses existing segmentation methodologies, demonstrating its efficacy in adapting large vision models for boundary-sensitive medical imaging tasks. The code is publicly available at https://github.com/IMOP-lab/MD-DERFS-Pytorch.git.
Keyword:
Ophthalmology
Optical Coherence Tomography
Retinal fluid
Macular edema
Large vision model
期刊
IF:
11.8
论文数:
3.9K
被引数:
2.4W
机构
引用论文
分享收藏Clinically applicable deep learning for diagnosis and referral in retinal disease深度学习在视网膜疾病诊断和转诊中的临床应用.png)
NATURE MEDICINE
NATURE MEDICINEIF50
PREAI
分享收藏Deep structure tensor graph search framework for automated extraction and characterization of retinal layers and fluid pathology in retinal SD-OCT scans用于视网膜sd-oct扫描中视网膜层和流体病理的自动提取和表征的深度结构张量图搜索框架
PREAI
分享收藏Electrochemically assisted micro localized grafting of aptamers in a microchannel engraved in fluorinated thermoplastic polymer Dyneon THVRSC Advances
RSC AdvancesIF0
PREAI
分享收藏Comparative study of layer by layer assembled multilayer films based on graphene oxide and reduced graphene oxide on flexible polyurethane foam: flame retardant and smoke suppression propertiesRSC Advances
RSC AdvancesIF0
PREAI
分享收藏Distant regulatory elements in a Sox10‐βGEO BAC transgene are required for expression of Sox10 in the enteric nervous system and other neural crest‐derived tissuesSox10-βgeo BAC转基因中的远距离调控元件是肠神经系统和其他神经源性组织中 Sox10 表达所必需的
OAAI
OAAI分享收藏
查看更多内容