Ultrasound image segmentation: a survey <s> A. Cardiology <s> A real time volumetric ultrasound imaging system has been developed for medical diagnosis. The scanner produces images analogous to an optical camera and supplies more information than conventional sonograms. Potential medical applications include improved anatomic visualization, tumor localization, and better assessment of cardiac function. The system uses pulse-echo phased array principles to steer a two-dimensional array transducer of 289 elements in a pyramidal scan format. Parallel processing in the receive mode produces 4992 scan lines at a rate of approximately B frames/second. Echo data for the scanned volume is presented as projection images with depth perspective, stereoscopic pairs, multiple tomographic images, or C-mode scans. <s> BIB001 </s> Ultrasound image segmentation: a survey <s> A. Cardiology <s> A basic goal in the analysis of echocardiographic images is to identify the locations of the endocardial borders. This is necessary in order to create three-dimensional reconstructions, and to derive precise quantitative parameters from the images. Endocardial borders can be identified manually; however, this is time-consuming, inconvenient, and liable to human subjectivity. For this reason there has been a great deal of interest in automatic border identification methods. In recent years numerous studies have been published, describing a wide variety of proposed border identification algorithms. In spite of the large number of published studies, however, the relative merits of the various methods remain unclear. In this paper the various analysis techniques are reviewed and discussed. The reasons for the lack of definitive conclusions regarding the utility of these methods are described. Finally, the basic methodological requirements necessary for empirical evaluation of border identification techniques are described. <s> BIB002 </s> Ultrasound image segmentation: a survey <s> A. Cardiology <s> Three-dimensional (3-D) imaging of the heart is a rapidly developing area of research in medical imaging. Advances in hardware and methods for fast spatio-temporal cardiac imaging are extending the frontiers of clinical diagnosis and research on cardiovascular diseases. In the last few years, many approaches have been proposed to analyze images and extract parameters of cardiac shape and function from a variety of cardiac imaging modalities. In particular, techniques based on spatio-temporal geometric models have received considerable attention. This paper surveys the literature of two decades of research on cardiac modeling. The contribution of the paper is three-fold: (1) to serve as a tutorial of the field for both clinicians and technologists, (2) to provide an extensive account of modeling techniques in a comprehensive and systematic manner, and (3) to critically review these approaches in terms of their performance and degree of clinical evaluation with respect to the final goal of cardiac functional analysis. From this review it is concluded that whereas 3-D model-based approaches have the capability to improve the diagnostic value of cardiac images, issues as robustness, 3-D interaction, computational complexity and clinical validation still require significant attention. <s> BIB003
Echocardiography (ultrasound imaging of the heart) has been one of the driving application areas of medical ultrasound and the literature on methods for automatically segmenting and tracking the left ventricle (the normal chamber assessed for heart disease) is extensive. Most attention has been given to tracking the motion of the endocardium (blood pool/tissue border) to allow for estimation of left ventricular areas/volumes and derived measures such as the ejection fraction, 1 and for regional wall motion assessment. In particular, these measures are used in diagnosis and assessment of ischaemic heart disease. Most analysis is based on 2-D acquisitions in which it is implicitly assumed that the principal component of motion is in the plane of the acquisition slice. The standard 2-D diagnostic views used for this are called the parasternal short-axis (SAX), and apical four-chamber (4C), two-chamber (2C), and three-chamber (3C) views. The latter three are also sometimes referred to as (apical) long-axis (LAX) views. The quality of data, and hence challenges for segmentation, vary depending on the view due to the anisotropy of ultrasound image acquisition, artefacts such as shadowing from the lungs, and attenuation which can be strong. Segmentation methods should also have strategies for avoiding the papillary muscles. Reliably finding the outer wall (often called epicardial border detection) is much more challenging, particularly from apical views. There are many papers on left ventricle tracking which deal with the tracking/deformation model independent of feature extraction or the imaging modality. We have not discussed these papers. See the review by Frangi et al. BIB003 for a discussion of this. Three-dimensional echocardiography is a relatively new imaging modality and image analysis is not yet well-developed. Early work used either freehand ultrasound (with 2-D image acquisition synchronized with recording the location of the slice with a position sensor), rotational 3-D probes which acquired a sparse set of 2-D image sequences, or real-time 3-D echocardiography based on the Volumetrics system BIB001 ,  . However, a second generation of real-time 3-D echocardiography systems have recently been produced by Philips Medical Systems. This data is of higher quality than the rotational 3-D probe and Volumetrics systems  . One, therefore, has to take particular care in interpreting the results from early 3-D work as being representative of what can be achieved today. This paper focuses on endocardial border detection unless otherwise stated. Much of the early work focused on still (single) frame segmentation-simulating what a cardiologist often does which is look at end-diastole (maximum expansion) and end-systole (maximum contraction) frames to compute measures such as the ejection fraction. 1 However, to fully assess heart function, analysis needs to be done over the whole cardiac cycle. Cardiologists also use a movie of a heart in decision-making as the speckle pattern associated with deforming tissue can be observed in a movie whereas in a still frame the speckle pattern is not always useful. As a result, and in contrast to some other clinical application areas (see later sections), in echocardiography it is perhaps more logical to view segmentation as a spatio-temporal problem. More recent successful approaches have taken this viewpoint. An early review of endocardial border detection is presented in BIB002 . However, in the intervening seven years or so there has been extensive research and progress in this area. Examples of segmentation results are illustrated in Fig. 1 .