Automated segmentation of transcranial sonographic images in the diagnostics of Parkinson’s disease Andrius Sakalauskas a,⇑ , Ar  unas Lukoševic ˇius a , Kristina Lauc ˇkaite ˙ b , Darius Jegelevic ˇius a Saulius Rutkauskas c a Biomedical Engineering Institute, Kaunas University of Technology, Studentu Str. 65, Kaunas LT-51359, Lithuania b Lithuanian University of Health Sciences, Department of Neurology, Academy of Medicine, Eiveniu Str. 2, Kaunas LT-50009, Lithuania c Lithuanian University of Health Sciences, Department of Radiology, Academy of Medicine, Eiveniu Str. 2, Kaunas LT-50009, Lithuania article info Article history: Received 9 August 2011 Received in revised form 29 March 2012 Accepted 15 April 2012 Available online xxxx Keywords: Transcranial sonography Image segmentation Speckle noise Averaging frames Active contours abstract Images captured during routine clinical transcranial sonography (TCS) examination are of a low resolu- tion, so can be confusing for diagnostic evaluations. Manual segmentation of brain structures (areas of the midbrain and substantia nigra (SN)) that are of special interest cause inter-observer and intra-obser- ver variability, thus restricting the reliability of Parkinson disease (PD) diagnostics. This paper presents a new technique for automated segmentation applicable to low resolution sonographic images, and partic- ularly to brain structures related to PD. The segmentation was performed by a modified shape-based active contour (AC) segmentation algorithm. In order to suppress the speckle noise and to improve the AC segmentation, a pre-processing technique based on the averaging of adjusted spatially varying TCS images is proposed. The latter technique was tested on clinical TCS images. The results of the automated segmentation were compared with the manual markings. Two experts on the 40 TCS images performed these markings. The comparison showed that an automated method is effective when segmentation of the midbrain is performed (averaged overlap between regions obtained automatically and outlined man- ually was 73.10 ± 7.45%). The results of the segmentation of the SN area showed that a sufficiently correct contour of this area could also be obtained, but the accuracy of the segmentation is related to the image quality. It should be emphasised that the main difficulty in evaluating the accuracy of automated seg- mentation of the SN was the indefinite ‘‘gold standard’’ (variation between the measurements of two experts with different experience was found). And, therefore, the diagnostic reliability of the proposed technique was inconclusive. Ó 2012 Elsevier B.V. All rights reserved. 1. Introduction The problem of limited resolution is quite common in ultra- sonic medical sonography since ultrasonic image quality is deci- sive for reliability in diagnostics. In particular cases, limited resolution is an especially hard issue to solve, one of which is transcranial B – mode sonography (TCS). TCS is a diagnostic tech- nique for supporting the clinical diagnosis of Parkinson’s disease (PD) as was proposed in 1995, by Berg [1]. Initial results revealed that TCS has the potential to become a powerful tool in diagnostics of various neurological movement disorders. It is assumed that the early stages of PD can be diagnosed by using TCS [2]. But scanning of the deep brain structures through the skull bone inevitably causes specific problems with image quality, particularly when scanning a butterfly-shaped midbrain and the small areas of the midbrain called the mesencephalic substantia nigra (SN) where neurotransmitter dopamine is produced – the region of interest (ROI) during TCS examination. Hyperechogenicity of the SN in the cross-sections of the midbrain is thought to be a characteristic feature for PD patients in the B – mode TCS images. Several re- searches [1–3] had shown that the size of the echogenic SN area of PD affected patients was larger than in healthy people. It was shown also that hyperechogenicity of the SN area is found in up to 90% of patients with PD [1]. The majority of authors recommend diagnosing neurological disorder when the SN area exceeds 0.20 cm 2 (S SN > 0.20 cm 2 ) [3]. Ultrasonic examination is quick, relatively cheap and harmless to the patient. However, one of the main drawbacks of TCS exam- ination is a spatial resolution of TCS images that is much lower compared with the ultrasound images obtained during scanning of the soft tissue: an axial resolution obtained in TCS images is 0.7–1.0 mm and the lateral resolution is approximately 3.0 mm [4] at a 6–9 cm depth where the ROI structures are located, mean- while, the resolution measured using soft tissue mimicking phan- tom is approximately 0.5–1.0 mm, 1.0–1.5 mm respectively 0041-624X/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ultras.2012.04.005 ⇑ Corresponding author. E-mail address: sakalauskas.andrius@yahoo.com (A. Sakalauskas). Ultrasonics xxx (2012) xxx–xxx Contents lists available at SciVerse ScienceDirect Ultrasonics journal homepage: www.elsevier.com/locate/ultras Please cite this article in press as: A. Sakalauskas et al., Automated segmentation of transcranial sonographic images in the diagnostics of Parkinson’s dis- ease, Ultrasonics (2012), http://dx.doi.org/10.1016/j.ultras.2012.04.005