Boundary-Guided and Region-Aware Network With Global Scale-Adaptive for Accurate Segmentation of Breast Tumors in Ultrasound Images

Hu, Kai; Zhou, Xiang; Xiong, Daxi; Zhang, Yuan; Gao, Xieping

doi:10.1109/jbhi.2023.3285789

Cited by 14 publications

(2 citation statements)

References 43 publications

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“…Aiming at the problem of blurred boundaries, Hu et al (2023) proposed a BUS image segmentation method using a boundary-guided and region-aware network with global scale-adaptive, and designed a boundary-guided module to improve boundary segmentation. Li et al (2023) constructed a feedback refinement boundary network FRBNet, consisting of a channel calibration module, the boundary detection (BD) module, and the feedback refinement module.…”

Section: Small Scale and Blurred Boundary Problems In Tumor Segmentationmentioning

confidence: 99%

Automatic breast ultrasound (ABUS) tumor segmentation based on global and local feature fusion

Li,

Ren,

Cheng

et al. 2024

Phys. Med. Biol.

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Accurate segmentation of tumor regions in automated breast ultrasound (ABUS) images is of paramount importance in computer-aided diagnosis (CAD) system. However, the inherent diversity of tumors and the imaging interference pose great challenges to ABUS tumor segmentation. In this paper, we propose a global and local feature interaction model combined with graph fusion (GLGM), for 3D ABUS tumor segmentation. In GLGM, we construct a dual branch encoder-decoder, where both local and global features can be extracted. Besides, a global and local feature fusion (GLFF) module is designed, which employs the deepest semantic interaction to facilitate information exchange between local and global features. Additionally, to improve the segmentation performance for small tumors, a graph convolution-based shallow feature fusion module (SFFGC) is designed. It exploits the shallow feature to enhance the feature expression of small tumors in both local and global domains. The proposed method is evaluated on a private ABUS dataset and a public ABUS dataset. For the private ABUS dataset, the small tumors (volume smaller than 1 cm³) account for over 50% of the entire dataset. Experimental results show that the proposed GLGM model outperforms several state-of-the-art segmentation models in 3D ABUS tumor segmentation, particularly in segmenting small tumors.

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Section: Small Scale and Blurred Boundary Problems In Tumor Segmentationmentioning

confidence: 99%

Automatic breast ultrasound (ABUS) tumor segmentation based on global and local feature fusion

Li,

Ren,

Cheng

et al. 2024

Phys. Med. Biol.

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“…Based on the above-mentioned directions of tumor diagnosis and treatment, 2D materials have had relatively important development and progress in the above fields in the past period of time (Liu et al, 2023b;Brevi and Zarrinpar, 2023;Kong et al, 2023;Meng et al, 2023) (Figure 1). In this review, we will provide an updated overview of the latest advancements in the application of 2D layer materials in tumor diagnosis and treatment, from a perspective that combines both fundamental research and hopeful clinical translation (Hu et al, 2023). In terms of elemental composition, ultra-thin and even atomthick 2D material sheets with almost only a single atom thickness can be divided into: graphene, transition metal sulfides, metal nitrides, double hydroxide, etc.…”

Section: Introductionmentioning

confidence: 99%

Advances in the two-dimensional layer materials for cancer diagnosis and treatment: unique advantages beyond the microsphere

Zhang,

Yang,

et al. 2023

Front. Bioeng. Biotechnol.

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In recent years, two-dimensional (2D) layer materials have shown great potential in the field of cancer diagnosis and treatment due to their unique structural, electronic, and chemical properties. These non-spherical materials have attracted increasing attention around the world because of its widely used biological characteristics. The application of 2D layer materials like lamellar graphene, transition metal dichalcogenides (TMDs), and black phosphorus (BPs) and so on have been developed for CT/MRI imaging, serum biosensing, drug targeting delivery, photothermal therapy, and photodynamic therapy. These unique applications for tumor are due to the multi-variable synthesis of 2D materials and the structural characteristics of good ductility different from microsphere. Based on the above considerations, the application of 2D materials in cancer is mainly carried out in the following three aspects: 1) In terms of accurate and rapid screening of tumor patients, we will focus on the enrichment of serum markers and sensitive signal transformation of 2D materials; 2) The progress of 2D nanomaterials in tumor MRI and CT imaging was described by comparing the performance of traditional contrast agents; 3) In the most important aspect, we will focus on the progress of 2D materials in the field of precision drug delivery and collaborative therapy, such as photothermal ablation, sonodynamic therapy, chemokinetic therapy, etc. In summary, this review provides a comprehensive overview of the advances in the application of 2D layer materials for tumor diagnosis and treatment, and emphasizes the performance difference between 2D materials and other types of nanoparticles (mainly spherical). With further research and development, these multifunctional layer materials hold great promise in the prospects, and challenges of 2D materials development are discussed.

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Quantifying the Economic Benefits of Agricultural Extension Services

Kumar,

Pradeepa

et al. 2024

Mathematical Modeling in Agriculture

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Boundary-Guided and Region-Aware Network With Global Scale-Adaptive for Accurate Segmentation of Breast Tumors in Ultrasound Images

Cited by 14 publications

References 43 publications

Automatic breast ultrasound (ABUS) tumor segmentation based on global and local feature fusion

Automatic breast ultrasound (ABUS) tumor segmentation based on global and local feature fusion

Advances in the two-dimensional layer materials for cancer diagnosis and treatment: unique advantages beyond the microsphere

Quantifying the Economic Benefits of Agricultural Extension Services

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