DCD: A Semantic Segmentation Model for Fetal Ultrasound Four-Chamber View

2025-06-10 · Donglian Li, Hui Guo, Minglang Chen, Huizhen Chen, Jialing Chen, Bocheng Liang, Pengchen Liang, Ying Tan

Accurate segmentation of anatomical structures in the apical four-chamber (A4C) view of fetal echocardiography is essential for early diagnosis and prenatal evaluation of congenital heart disease (CHD). However, precise segmentation remains challenging due to ultrasound artifacts, speckle noise, anatomical variability, and boundary ambiguity across different gestational stages. To reduce the workload of sonographers and enhance segmentation accuracy, we propose DCD, an advanced deep learning-based model for automatic segmentation of key anatomical structures in the fetal A4C view. Our model incorporates a Dense Atrous Spatial Pyramid Pooling (Dense ASPP) module, enabling superior multi-scale feature extraction, and a Convolutional Block Attention Module (CBAM) to enhance adaptive feature representation. By effectively capturing both local and global contextual information, DCD achieves precise and robust segmentation, contributing to improved prenatal cardiac assessment.

📄 PDF Abstract BibTeX arXiv:2506.08534

Code (0)

등록된 구현이 없습니다.

Tasks

Segmentation Semantic Segmentation

Methods 이 논문이 사용한 방법론

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Attention 설명 없음

Spatial Pyramid Pooling Spatial Pyramid Pooling (SPP) is a pooling layer that removes the fixed-size constraint of the network, i.e. a CNN does not require a fixed-size input image. Specifically, we…

Automatic Detection of Cardiac Chambers Using an Attention-based YOLOv4 Framework from Four-chamber View of Fetal Echocardiography

2020-11-26 · Sibo Qiao, Shanchen Pang, Gang Luo, Silin Pan 외

Echocardiography is a powerful prenatal examination tool for early diagnosis of fetal congenital heart diseases (CHDs). The four-chamber (FC) view is a crucial and easily accessible ultrasound (US) image among echocardio…

Multiview and Multiclass Image Segmentation using Deep Learning in Fetal Echocardiography

2021-03-23 · Ken C. L. Wong, Elena S. Sinkovskaya, Alfred Z. Abuhamad, Tanveer Syeda-Mahmood

Congenital heart disease (CHD) is the most common congenital abnormality associated with birth defects in the United States. Despite training efforts and substantial advancement in ultrasound technology over the past yea…

Image Segmentation Segmentation Semantic Segmentation

Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps

2021-07-06 · Samuel Budd, Matthew Sinclair, Thomas Day, Athanasios Vlontzos 외

Fetal ultrasound screening during pregnancy plays a vital role in the early detection of fetal malformations which have potential long-term health impacts. The level of skill required to diagnose such malformations from …

Disease Prediction image-classification Image Classification Image Segmentation+2

AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes

2021-07-12 · Sophia Bano, Brian Dromey, Francisco Vasconcelos, Raffaele Napolitano 외

During pregnancy, ultrasound examination in the second trimester can assess fetal size according to standardized charts. To achieve a reproducible and accurate measurement, a sonographer needs to identify three standard …

Anatomy Segmentation

UniFLM: United Segmentation and Measurement on Fetal Limb Ultrasonic Image

2026-08-27 · Zeen Zhou, Qiuhua Chen, Xiaojun Cao, Changmao Chen 외 arxiv

Prenatal ultrasound examination is crucial for assessing fetal limb development and detecting congenital anomalies. However, existing artificial intelligence models often overlook fetal lethal skeletal dysplasias due to …