Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks

Bargsten, Lennart; Riedl, Katharina; Wissel, Tobias; Brunner, Fabian J.; Schaefers, Klaus; Sprenger, Johanna; Graß, Michael; Seiffert, Moritz; Blankenberg, Stefan; Schlaefer, Alexander

doi:10.1117/12.2580720

Search citation statements

Order By: Relevance

Paper Sections

Select...

Advanced Us Imaging In Cardiology and DL Techniques1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

2022

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To further improve the performance and the generalizability of CNNs for the IVUS segmentation, Bargsten et al [ 87 ] applied anatomical constraints to train a U-net architecture. These constraints were represented by regularization terms which considered some prior knowledge about the lumen and vessel wall, such as location and shape.…”

Section: Advanced Us Imaging In Cardiology and DL Techniquesmentioning

confidence: 99%

Advanced Ultrasound and Photoacoustic Imaging in Cardiology

Awasthi

Rad

et al. 2021

Sensors

View full text Add to dashboard Cite

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide. An effective management and treatment of CVDs highly relies on accurate diagnosis of the disease. As the most common imaging technique for clinical diagnosis of the CVDs, US imaging has been intensively explored. Especially with the introduction of deep learning (DL) techniques, US imaging has advanced tremendously in recent years. Photoacoustic imaging (PAI) is one of the most promising new imaging methods in addition to the existing clinical imaging methods. It can characterize different tissue compositions based on optical absorption contrast and thus can assess the functionality of the tissue. This paper reviews some major technological developments in both US (combined with deep learning techniques) and PA imaging in the application of diagnosis of CVDs.

show abstract

Section: Advanced Us Imaging In Cardiology and DL Techniquesmentioning

confidence: 99%