Breast ultrasound image segmentation: a survey

Purpose

Breast cancer is the most common form of cancer among women worldwide. Ultrasound imaging is one of the most frequently used diagnostic tools to detect and classify abnormalities of the breast. Recently, computer-aided diagnosis (CAD) systems using ultrasound images have been developed to help radiologists to increase diagnosis accuracy. However, accurate ultrasound image segmentation remains a challenging problem due to various ultrasound artifacts. In this paper, we investigate approaches developed for breast ultrasound (BUS) image segmentation.

Methods

In this paper, we reviewed the literature on the segmentation of BUS images according to the techniques adopted, especially over the past 10 years. By dividing into seven classes (i.e., thresholding-based, clustering-based, watershed-based, graph-based, active contour model, Markov random field and neural network), we have introduced corresponding techniques and representative papers accordingly.

Results

We have summarized and compared many techniques on BUS image segmentation and found that all these techniques have their own pros and cons. However, BUS image segmentation is still an open and challenging problem due to various ultrasound artifacts introduced in the process of imaging, including high speckle noise, low contrast, blurry boundaries, low signal-to-noise ratio and intensity inhomogeneity

Conclusions

To the best of our knowledge, this is the first comprehensive review of the approaches developed for segmentation of BUS images. With most techniques involved, this paper will be useful and helpful for researchers working on segmentation of ultrasound images, and for BUS CAD system developers.

     

Ultrasound speckle reduction based on fractional order differentiation

Purpose

Ultrasound images show a granular pattern of noise known as speckle that diminishes their quality and results in difficulties in diagnosis. To preserve edges and features, this paper proposes a fractional differentiation-based image operator to reduce speckle in ultrasound.

Methods

An image de-noising model based on fractional partial differential equations with balance relation between k (gradient modulus threshold that controls the conduction) and v (the order of fractional differentiation) was constructed by the effective combination of fractional calculus theory and a partial differential equation, and the numerical algorithm of it was achieved using a fractional differential mask operator.

Results

The proposed algorithm has better speckle reduction and structure preservation than the three existing methods [P-M model, the speckle reducing anisotropic diffusion (SRAD) technique, and the detail preserving anisotropic diffusion (DPAD) technique]. And it is significantly faster than bilateral filtering (BF) in producing virtually the same experimental results.

Conclusions

Ultrasound phantom testing and in vivo imaging show that the proposed method can improve the quality of an ultrasound image in terms of tissue SNR, CNR, and FOM values.

     

Synthetic aperture ultrasound imaging with a ring transducer array: preliminary ex vivo results

Purpose

The conventional medical ultrasound imaging has a low lateral spatial resolution, and the image quality depends on the depth of the imaging location. To overcome these problems, this study presents a synthetic aperture (SA) ultrasound imaging method using a ring transducer array.

Methods

An experimental ring transducer array imaging system was constructed. The array was composed of 2048 transducer elements, and had a diameter of 200 mm and an inter-element pitch of 0.325 mm. The imaging object was placed in the center of the ring transducer array, which was immersed in water. SA ultrasound imaging was then employed to scan the object and reconstruct the reflection image.

Results

Both wire phantom and ex vivo experiments were conducted. The proposed method was found to be capable of producing isotropic high-resolution images of the wire phantom. In addition, preliminary ex vivo experiments using porcine organs demonstrated the ability of the method to reconstruct high-quality images without any depth dependence.

Conclusion

The proposed ring transducer array and SA ultrasound imaging method were shown to be capable of producing isotropic high-resolution images whose quality was independent of depth.

     

Multi-ray medical ultrasound simulation without explicit speckle modelling

Purpose

To develop a medical ultrasound (US) simulation method using T1-weighted magnetic resonance images (MRI) as the input that offers a compromise between low-cost ray-based and high-cost realistic wave-based simulations.

Methods

The proposed method uses a novel multi-ray image formation approach with a virtual phased array transducer probe. A domain model is built from input MR images. Multiple virtual acoustic rays are emerged from each element of the linear transducer array. Reflected and transmitted acoustic energy at discrete points along each ray is computed independently. Simulated US images are computed by fusion of the reflected energy along multiple rays from multiple transducers, while phase delays due to differences in distances to transducers are taken into account. A preliminary implementation using GPUs is presented.

Results

Preliminary results show that the multi-ray approach is capable of generating view point-dependent realistic US images with an inherent Rician distributed speckle pattern automatically. The proposed simulator can reproduce the shadowing artefacts and demonstrates frequency dependence apt for practical training purposes. We also have presented preliminary results towards the utilization of the method for real-time simulations.

Conclusions

The proposed method offers a low-cost near-real-time wave-like simulation of realistic US images from input MR data. It can further be improved to cover the pathological findings using an improved domain model, without any algorithmic updates. Such a domain model would require lesion segmentation or manual embedding of virtual pathologies for training purposes.

     

First step to facilitate long-term and multi-centre studies of shear wave elastography in solid breast lesions using a computer-assisted algorithm

Purpose

Shear wave elastography (SWE) visualises the elasticity of tissue. As malignant tissue is generally stiffer than benign tissue, SWE is helpful to diagnose solid breast lesions. Until now, quantitative measurements of elasticity parameters have been possible only, while the images were still saved on the ultrasound imaging device. This work aims to overcome this issue and introduces an algorithm allowing fast offline evaluation of SWE images.

Methods

The algorithm was applied to a commercial phantom comprising three lesions of various elasticities and 207 in vivo solid breast lesions. All images were saved in DICOM, JPG and QDE (quantitative data export; for research only) format and evaluated according to our clinical routine using a computer-aided diagnosis algorithm. The results were compared to the manual evaluation (experienced radiologist and trained engineer) regarding their numerical discrepancies and their diagnostic performance using ROC and ICC analysis.

Results

ICCs of the elasticity parameters in all formats were nearly perfect (0.861–0.990). AUC for all formats was nearly identical for \({E}_{\mathrm{max}}\) and \({E}_{\mathrm{mean}}\) (0.863–0.888). The diagnostic performance of SD using DICOM or JPG estimations was lower than the manual or QDE estimation (AUC 0.673 vs. 0.844).

Conclusions

The algorithm introduced in this study is suitable for the estimation of the elasticity parameters offline from the ultrasound system to include images taken at different times and sites. This facilitates the performance of long-term and multi-centre studies.

     

Shading correction for endoscopic images using principal color components

Purpose

Inhomogeneous illumination often causes significant shading and vignetting effects in images captured by an endoscope. Most of the established shading correction methods are designed for gray-level images. Only few papers have been published about how to compensate for shading in color images. For endoscopic images with a distinct red coloring, these methods tend to produce color artifacts.

Method

A color shading correction algorithm for endoscopic images is proposed. Principal component analysis is used to calculate an appropriate estimate of the shading effect so that a one-channel shading correction can be applied without producing undesired artifacts.

Results

The proposed method is compared to established YUV and HSV color-conversion-based approaches. It produces superior results both on simulated and on real endoscopic images. Example images of using the proposed shading correction for endoscopic image mosaicking are presented.

Conclusion

A new method for shading correction is presented which is tailored to images with distinct coloring. It is beneficial for the visual impression and further image analysis tasks.

     

Reproducibility of acquiring ultrasonographic infant hip images by the Graf method after an infant hip ultrasound training course

Purpose

The objective screening of infant hips using ultrasonography (Graf method) is gaining favor in the diagnosis of developmental dysplasia of the hip in Japan. However, the accuracy of the Graf method is dependent on the examiner’s experience and technique. The purpose of this study was to investigate the reproducibility of acquiring ultrasonic hip images and their evaluation after examiners attended an infant hip ultrasound training course.

Materials and methods

Ultrasonic images of 70 hips of 35 newborns who were screened by ultrasonography using the Graf method, were evaluated. The images were acquired by two inexperienced examiners who attended the training course. The inter- and intra-examiner measurement errors as well as reproducibility were calculated based on the images obtained.

Results

The intra-examiner measurement error in the acquired images of the same hip was minor. The inter-examiner measurement error was also small. The intra- and inter-examiner agreements of the Graf classification were high. The intra-examiner reproducibility of the acquired ultrasonic images was substantial, and the inter-examiner reproducibility was almost perfect.

Conclusions

Our results demonstrated that inexperienced examiners could obtain ultrasonic infant hip joint images with minor differences and high reproducibility after the training course. Our findings raise the possibility of extending the infant hip ultrasound course in Japan.

     

Ultrasound thermal monitoring with an external ultrasound source for customized bipolar RF ablation shapes

Purpose

Thermotherapy is a clinical procedure which delivers thermal energy to a target, and it has been applied for various medical treatments. Temperature monitoring during thermotherapy is important to achieve precise and reproducible results. Medical ultrasound can be used for thermal monitoring and is an attractive medical imaging modality due to its advantages including non-ionizing radiation, cost-effectiveness and portability. We propose an ultrasound thermal monitoring method using a speed-of-sound tomographic approach coupled with a biophysical heat diffusion model.

Methods

We implement an ultrasound thermometry approach using an external ultrasound source. We reconstruct the speed-of-sound images using time-of-flight information from the external ultrasound source and convert the speed-of-sound information into temperature by using the a priori knowledge brought by a biophysical heat diffusion model.

Results

Customized treatment shapes can be created using switching channels of radio frequency bipolar needle electrodes. Simulations of various ablation lesion shapes in the temperature range of 21–59 \(^\circ \)C are performed to study the feasibility of the proposed method. We also evaluated our method with ex vivo porcine liver experiments, in which we generated temperature images between 22 and 45 \(^\circ \)C.

Conclusion

In this paper, we present a proof of concept showing the feasibility of our ultrasound thermal monitoring method. The proposed method could be applied to various thermotherapy procedures by only adding an ultrasound source.

     

An automatic segmentation method of a parameter-adaptive PCNN for medical images

Purpose

Since pre-processing and initial segmentation steps in medical images directly affect the final segmentation results of the regions of interesting, an automatic segmentation method of a parameter-adaptive pulse-coupled neural network is proposed to integrate the above-mentioned two segmentation steps into one. This method has a low computational complexity for different kinds of medical images and has a high segmentation precision.

Methods

The method comprises four steps. Firstly, an optimal histogram threshold is used to determine the parameter \(\alpha \) for different kinds of images. Secondly, we acquire the parameter \(\beta \) according to a simplified pulse-coupled neural network (SPCNN). Thirdly, we redefine the parameter V of the SPCNN model by sub-intensity distribution range of firing pixels. Fourthly, we add an offset \(A\times S_{\mathrm{off}}\) to improve initial segmentation precision.

Results

Compared with the state-of-the-art algorithms, the new method achieves a comparable performance by the experimental results from ultrasound images of the gallbladder and gallstones, magnetic resonance images of the left ventricle, and mammogram images of the left and the right breast, presenting the overall metric UM of 0.9845, CM of 0.8142, TM of 0.0726.

Conclusion

The algorithm has a great potential to achieve the pre-processing and initial segmentation steps in various medical images. This is a premise for assisting physicians to detect and diagnose clinical cases.

     

Impact of parametric imaging on contrast-enhanced ultrasound of breast cancer

Purpose

To prospectively evaluate the usefulness of contrast-enhanced ultrasound (CEUS) using parametric imaging for breast cancer in a multicenter study.

Methods

A total of 65 patients with breast cancer were included in this study. CEUS was performed, and still images on peak time (S), accumulated images (A) and parametric images (P) were generated from the raw data. Four blind reviewers ranked the best visible images as first place, and determined second and third place consecutively. We compared the average ranking of each image. The maximal diameter of the tumor determined on ultrasonography and MRI was compared with the corresponding pathological maximal diameter for 48 of the 65 patients. The correlation between the diameter determined by two experts and two beginners was analyzed.

Results

The average rank of visibility was as follows: P, 1.44; A, 2.04; and S, 2.52. The correlation between each image and the pathology was as follows: P, r = 0.664; A, r = 0.630; S, r = 0.717; and MRI, r = 0.936. There were no significant differences among the correlation between the experts and beginners in each image.

Conclusions

The use of parametric imaging improves the visibility of CEUS. The maximal diameter of the tumor determined on CEUS correlates substantially with the pathology.

     

SUPRA: open-source software-defined ultrasound processing for real-time applications

Purpose

Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing steps on such platforms.

Methods

With SUPRA, we propose an open-source pipeline for fully software-defined ultrasound processing for real-time applications to alleviate these problems. Covering all steps from beamforming to output of B-mode images, SUPRA can help improve the reproducibility of results and make modifications to the image acquisition mode accessible to the research community. We evaluate the pipeline qualitatively, quantitatively, and regarding its run time.

Results

The pipeline shows image quality comparable to a clinical system and backed by point spread function measurements a comparable resolution. Including all processing stages of a usual ultrasound pipeline, the run-time analysis shows that it can be executed in 2D and 3D on consumer GPUs in real time.

Conclusions

Our software ultrasound pipeline opens up the research in image acquisition. Given access to ultrasound data from early stages (raw channel data, radiofrequency data), it simplifies the development in imaging. Furthermore, it tackles the reproducibility of research results, as code can be shared easily and even be executed without dedicated ultrasound hardware.

     

Speckle Tracking Echocardiographic Imaging in Metabolic Cardiomyopathies

Purpose of Review

The aging population in western nations has experienced an increase in the prevalence of heart failure alongside the increasing rates of obesity, metabolic syndrome, and type 2 diabetes mellitus. Clinical studies have established a strong link between these metabolic derangements and the risk of heart failure.

Recent Findings

Echocardiography is an essential tool in supporting the diagnosis of heart failure and establishing its phenotype. Advanced echocardiographic methods based on speckle tracking echocardiography provide unique insights into myocardial mechanics and underlie the novel approach to phenotype classification of heart failure patients.

Summary

The current review summarizes the myocardial mechanics assessment based on speckle tracking echocardiography focusing on diabetic cardiomyopathy. It highlights potential applications and promises of this approach.

     

Consistent reconstruction of 4D fetal heart ultrasound images to cope with fetal motion

Purpose

4D ultrasound imaging of the fetal heart relies on reconstructions from B-mode images. In the presence of fetal motion, current approaches suffer from artifacts, which are unrecoverable for single sweeps.

Methods

We propose to use many sweeps and exploit the resulting redundancy to automatically recover from motion by reconstructing a 4D image which is consistent in phase, space, and time. An interactive visualization framework to view animated ultrasound slices from 4D reconstructions on arbitrary planes was developed using a magnetically tracked mock probe.

Results

We first quantified the performance of 10 4D reconstruction formulations on simulated data. Reconstructions of 14 in vivo sequences by a baseline, the current state-of-the-art, and the proposed approach were then visually ranked with respect to temporal quality on orthogonal views. Rankings from 5 observers showed that the proposed 4D reconstruction approach significantly improves temporal image quality in comparison with the baseline. The 4D reconstructions of the baseline and the proposed methods were then inspected interactively for accessibility to clinically important views and rated for their clinical usefulness by an ultrasound specialist in obstetrics and gynecology. The reconstructions by the proposed method were rated as ‘very useful’ in 71% and were statistically significantly more useful than the baseline reconstructions.

Conclusions

Multi-sweep fetal heart ultrasound acquisitions in combination with consistent 4D image reconstruction improves quality as well as clinical usefulness of the resulting 4D images in the presence of fetal motion.

     

User-friendly freehand ultrasound calibration using Lego bricks and automatic registration

Purpose

As an inexpensive, noninvasive, and portable clinical imaging modality, ultrasound (US) has been widely employed in many interventional procedures for monitoring potential tissue deformation, surgical tool placement, and locating surgical targets. The application requires the spatial mapping between 2D US images and 3D coordinates of the patient. Although positions of the devices (i.e., ultrasound transducer) and the patient can be easily recorded by a motion tracking system, the spatial relationship between the US image and the tracker attached to the US transducer needs to be estimated through an US calibration procedure. Previously, various calibration techniques have been proposed, where a spatial transformation is computed to match the coordinates of corresponding features in a physical phantom and those seen in the US scans. However, most of these methods are difficult to use for novel users.

Methods

We proposed an ultrasound calibration method by constructing a phantom from simple Lego bricks and applying an automated multi-slice 2D–3D registration scheme without volumetric reconstruction. The method was validated for its calibration accuracy and reproducibility.

Results

Our method yields a calibration accuracy of \(1.23\pm 0.26\) mm and a calibration reproducibility of 1.29 mm.

Conclusion

We have proposed a robust, inexpensive, and easy-to-use ultrasound calibration method.

     

Breast cancer cell nuclei classification in histopathology images using deep neural networks

Purpose

Cell nuclei classification in breast cancer histopathology images plays an important role in effective diagnose since breast cancer can often be characterized by its expression in cell nuclei. However, due to the small and variant sizes of cell nuclei, and heavy noise in histopathology images, traditional machine learning methods cannot achieve desirable recognition accuracy. To address this challenge, this paper aims to present a novel deep neural network which performs representation learning and cell nuclei recognition in an end-to-end manner.

Methods

The proposed model hierarchically maps raw medical images into a latent space in which robustness is achieved by employing a stacked denoising autoencoder. A supervised classifier is further developed to improve the discrimination of the model by maximizing inter-subject separability in the latent space. The proposed method involves a cascade model which jointly learns a set of nonlinear mappings and a classifier from the given raw medical images. Such an on-the-shelf learning strategy makes obtaining discriminative features possible, thus leading to better recognition performance.

Results

Extensive experiments with benign and malignant breast cancer datasets are conducted to verify the effectiveness of the proposed method. Better performance was obtained when compared with other feature extraction methods, and higher recognition rate was achieved when compared with other seven classification methods.

Conclusions

We propose an end-to-end DNN model for cell nuclei and non-nuclei classification of histopathology images. It demonstrates that the proposed method can achieve promising performance in cell nuclei classification, and the proposed method is suitable for the cell nuclei classification task.

     

Estimating needle tip deflection in biological tissue from a single transverse ultrasound image: application to brachytherapy

Purpose

This paper proposes a method to predict the deflection of a flexible needle inserted into soft tissue based on the observation of deflection at a single point along the needle shaft.

Methods

We model the needle-tissue as a discretized structure composed of several virtual, weightless, rigid links connected by virtual helical springs whose stiffness coefficient is found using a pattern search algorithm that only requires the force applied at the needle tip during insertion and the needle deflection measured at an arbitrary insertion depth. Needle tip deflections can then be predicted for different insertion depths.

Results

Verification of the proposed method in synthetic and biological tissue shows a deflection estimation error of \(<\)2 mm for images acquired at 35 % or more of the maximum insertion depth, and decreases to 1 mm for images acquired closer to the final insertion depth. We also demonstrate the utility of the model for prostate brachytherapy, where in vivo needle deflection measurements obtained during early stages of insertion are used to predict the needle deflection further along the insertion process.

Conclusion

The method can predict needle deflection based on the observation of deflection at a single point. The ultrasound probe can be maintained at the same position during insertion of the needle, which avoids complications of tissue deformation caused by the motion of the ultrasound probe.

     

Efficiency of quantitative echogenicity for investigating supraspinatus tendinopathy by the gray-level histogram of two ultrasound devices

Purpose

The gray-level histogram of ultrasound is a promising tool for scanning the hypoechogenic appearance of supraspinatus tendinopathy, and the aim of this study was to test the hypothesis that the gray-level value of the supraspinatus tendon in the painful shoulder has a lower value on B-mode images even though in different ultrasound devices.

Methods

Sixty-seven patients who had unilateral shoulder pain with rotator cuff tendinopathy underwent bilateral shoulder ultrasonography, and we compared the mean gray-level values of painful shoulders and contralateral shoulders without any pain in each patient using two ultrasound devices. The echogenicity ratio (symptomatic/asymptomatic side) of two ultrasound devices was compared.

Results

A significant difference existed between the symptomatic shoulder and contralateral asymptomatic shoulder (p < 0.001) on the mean gray-level value measurements of each device. The symptomatic-to-asymptomatic tendon echogenicity ratio of device A was 0.919 ± 0.090 in the transverse plane and 0.937 ± 0.081 in the longitudinal plane, and the echogenicity ratio of device B was 0.899 ± 0.113 in the transverse plane and 0.940 ± 0.113 in the longitudinal plane.

Conclusions

The decline of the mean gray-level value and the echogenicity ratio of the supraspinatus tendon in the painful shoulder may be utilized as a useful sonographic reference of unilateral rotator cuff lesions.

Level of evidence

Diagnostic level III.

     

A novel ultrasonic method for evaluation of blood clotting parameters

Purpose

For long time, blood clot retraction was measured only by thromboelastographic or platelet contractile force measurement techniques. The purpose of the present study was development of a novel ultrasonic method based on simultaneous monitoring of variations in the ultrasound velocity and the frequency spectrum of the signal propagating in clotting blood and its application for automatic evaluation of blood clotting parameters.

Methods

Simultaneous measurement of ultrasound velocity and variations in the frequency spectrum of wideband ultrasonic signals in clotting blood samples was performed. All measurements were performed in pulse-echo mode. Standard clinical data were obtained using routine clinical laboratory methods.

Results

The amplitudes of ultrasonic signals during native blood coagulation varied up to ten times for different frequencies. The measurement results of the start and duration of blood clot retraction differed between patient samples: different components of the blood coagulation system had significant impact on the blood clot retraction process.

Conclusions

Our results showed that during blood clotting, the ultrasound velocity and variations in frequency spectrum should be used simultaneously to determine the beginning and duration of blood clot retraction. Our results also showed that blood clot retraction is controlled by the activity of factor XIII.

     

Olanzapine vs haloperidol: treating delirium in a critical care setting

Objective

To compare the safety and estimate the response profile of olanzapine, a second-generation antipsychotic, to haloperidol in the treatment of delirium in the critical care setting.

Design

Prospective randomized trial

Setting

Tertiary care university affiliated critical care unit.

Patients

All admissions to a medical and surgical intensive care unit with a diagnosis of delirium.

Interventions

Patients were randomized to receive either enteral olanzapine or haloperidol.

Measurements

Patient’s delirium severity and benzodiazepine use were monitored over 5 days after the diagnosis of delirium.

Main results

Delirium Index decreased over time in both groups, as did the administered dose of benzodiazepines. Clinical improvement was similar in both treatment arms. No side effects were noted in the olanzapine group, whereas the use of haloperidol was associated with extrapyramidal side effects.

Conclusions

Olanzapine is a safe alternative to haloperidol in delirious critical care patients, and may be of particular interest in patients in whom haloperidol is contraindicated.