Extracting cardiac myofiber orientations from high frequency ultrasound images

Qin, Xulei; Cong, Zhi-Bin; Jiang, Rong; Shen, Ming; Wagner, Mary B.; Kishbom, Paul; Fei, Baowei

doi:10.1117/12.2006494

Cited by 13 publications

(15 citation statements)

References 22 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…508 nm and 510 nm in our case, were removed from the image cubes to avoid the effect of GFP signals on the classification process. Filtering methods may be used as a pre-processing step to reduce noise in images [20] [21]. …”

Section: Methodsmentioning

confidence: 99%

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging

Halig

Wang

et al. 2014

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

As an emerging technology, hyperspectral imaging (HSI) combines both the chemical specificity of spectroscopy and the spatial resolution of imaging, which may provide a non-invasive tool for cancer detection and diagnosis. Early detection of malignant lesions could improve both survival and quality of life of cancer patients. In this paper, we introduce a tensor-based computation and modeling framework for the analysis of hyperspectral images to detect head and neck cancer. The proposed classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 96.97% and an average specificity of 91.42% in tumor-bearing mice. The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management.

show abstract

Section: Methodsmentioning

confidence: 99%

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging

Halig

Wang

et al. 2014

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

show abstract

“…During the ultrasound imaging procedure, the ultrasound probe pressed the heart and caused deformation. The fiber orientations also affected the ultrasound images and generated imaging artifacts [25, 26]. In order to correct the deformation, three deformable registration methods, i.e.…”

Section: Methodsmentioning

confidence: 99%

Mapping cardiac fiber orientations from high-resolution DTI to high-frequency 3D ultrasound

et al. 2014

Self Cite

View full text Add to dashboard Cite

The orientation of cardiac fibers affects the anatomical, mechanical, and electrophysiological properties of the heart. Although echocardiography is the most common imaging modality in clinical cardiac examination, it can only provide the cardiac geometry or motion information without cardiac fiber orientations. If the patient’s cardiac fiber orientations can be mapped to his/her echocardiography images in clinical examinations, it may provide quantitative measures for diagnosis, personalized modeling, and image-guided cardiac therapies. Therefore, this project addresses the feasibility of mapping personalized cardiac fiber orientations to three-dimensional (3D) ultrasound image volumes. First, the geometry of the heart extracted from the MRI is translated to 3D ultrasound by rigid and deformable registration. Deformation fields between both geometries from MRI and ultrasound are obtained after registration. Three different deformable registration methods were utilized for the MRI-ultrasound registration. Finally, the cardiac fiber orientations imaged by DTI are mapped to ultrasound volumes based on the extracted deformation fields. Moreover, this study also demonstrated the ability to simulate electricity activations during the cardiac resynchronization therapy (CRT) process. The proposed method has been validated in two rat hearts and three canine hearts. After MRI/ultrasound image registration, the Dice similarity scores were more than 90% and the corresponding target errors were less than 0.25 mm. This proposed approach can provide cardiac fiber orientations to ultrasound images and can have a variety of potential applications in cardiac imaging.

show abstract

“…4) which are also capable of visualizing LV septum. Other important imaging tools are histology [12, 78, 86], optical coherence tomography (OCT) [11, 17, 87, 88], multimodality imaging [16, 89, 90], second-harmonic generation (SHG) microscopy [10, 91], and susceptibility weight imaging (SWI) [92]. Table 1 provides a summary of the imaging methodologies that have been used to evaluate cardiac fiber arrangement in different species.…”

Section: Overview Of Imaging Technologies For Detecting Heart Failurementioning

confidence: 99%

“…The velocity data can be used for calculating parameters, such as the displacement, strain rate, and strain [102]. Therefore, cardiac ultrasound has an important role in the imaging of hearts in basic and clinical cardiovascular research [90] and remains the gold standard for cardiac function assessment. Ultrasound is often used in clinical cardiac examinations because it can provide real-time functional information regarding heart values and, similar to most three-dimensional imaging techniques, it has the capability to provide the geometry and motion information of the heart [103].…”

Section: Ultrasound Imagingmentioning

confidence: 99%

Imaging technologies for cardiac fiber and heart failure: a review

2018

Self Cite

View full text Add to dashboard Cite

There has been an increasing interest in studying cardiac fibers in order to improve the current knowledge regarding the mechanical and physiological properties of the heart during heart failure (HF), particularly early HF. Having a thorough understanding of the changes in cardiac fiber orientation may provide new insight into the mechanisms behind the progression of left ventricular (LV) remodeling and HF. We conducted a systematic review on various technologies for imaging cardiac fibers and its link to HF. This review covers literature reports from 1900 to 2017. PubMed and Google Scholar databases were searched using the keywords “cardiac fiber” and “heart failure” or “myofiber” and “heart failure.” This review highlights imaging methodologies, including magnetic resonance diffusion tensor imaging (MR-DTI), ultrasound, and other imaging technologies as well as their potential applications in basic and translational research on the development and progression of HF. MR-DTI and ultrasound have been most useful and significant in evaluating cardiac fibers and HF. New imaging technologies that have the ability to measure cardiac fiber orientations and identify structural and functional information of the heart will advance basic research and clinical diagnoses of HF.

show abstract

Extracting cardiac myofiber orientations from high frequency ultrasound images

Cited by 13 publications

References 22 publications

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging

Mapping cardiac fiber orientations from high-resolution DTI to high-frequency 3D ultrasound

Imaging technologies for cardiac fiber and heart failure: a review

Contact Info

Product

Resources

About