This paper compares two manual measurement

techniques for measuring retinal vessel segment widths: the

kick-points technique and the edge marking technique. An image

set of 164 clear, high-resolution segments was used. The

kick-points approach uses kick points marked by observers

along interpolated cross-sectional intensity profile graphs; the

edge marking method allows observers to nominate the edges on

a zoomed-up image, and interpolates edge positions. The edgemarking

method provides more precise measurements than the

kick-points method, but these are subject to more inter-observer

variability; we speculate that this result is due to differing observer

perceptions of the edge location

Al-Diri, Bashir

Hunter, Andrew

English

University of Lincoln Institutional Repository

Accurate Methods for Manually Marking Retinal Vessel WidthsBashir Al-Diri1, Andrew Hunter1 and David Steel21 Lincoln School of Computer Science, University of Lincoln, Lincoln, UK2 Sunderland Eye Infirmary, Sunderland, UKAbstract— This paper compares two manual measurementtechniques for measuring retinal vessel segment widths: thekick-points technique and the edge marking technique. An im-age set of 164 clear, high-resolution segments was used. Thekick-points approach uses kick points marked by observersalong interpolated cross-sectional intensity profile graphs; theedge marking method allows observers to nominate the edges ona zoomed-up image, and interpolates edge positions. The edge-marking method provides more precise measurements than thekick-points method, but these are subject to more inter-observervariability; we speculate that this result is due to differing ob-server perceptions of the edge location.Keywords— Retinal vessel, kick points, measuring vessel width,manual measurement.I. INTRODUCTIONThis paper presents a preliminary analysis of two man-ual techniques for the measurement of retinal vessel widths:the edge-point marking technique (EPMT) [1] and the kick-point marking technique (KPMT) [2], showing that EPMTgives width measurements with lower variance and higherbias than KPMT. Given that variation in width rather thanabsolute width is important in the characterization of disease,we argue that this shows EPMT to be a superior manual mea-surement technique to KPMT. In addition, EPMT automati-cally determines the profile direction.Both EPMT and KPMT are methods to support the mark-ing of retinal edge vessel widths by a human observer. Man-ual marking is of interest for two reasons: to provide groundtruths [3] to support the development of automated widthmeasurement algorithms, and to allow the accurate study ofthe relationship between retinal disease and vessel geometry.The simplest approach to manual retinal vessel width mea-surement is to require the observer to nominate two points,one on each edge of the vessel [1]. This requires the observerboth to correctly place the points on the vessel edges, and toensure that they lie on a single profile line – that is, a lineorthogonal to the vessel direction. There are thus two possi-ble sources of error: inaccurate edge marking, and inaccuratedetermination of profile direction. Given that the observer istypically limited to nominating at pixel resolution, and retinalvessels are often only a few pixels across, the approach is alsoprone to discretization errors, both in width and angle nomi-nation. Accuracy can be improved by first drawing a profileline orthogonal to the vessel, and then nominating the inter-section with the edges, and by averaging multiple measure-ments taken along a short section of the vessel, using parallelprofile lines.A more advance technique is based on the “kick point”phenomena. The blood vessels absorb some of the funduscamera light reflected from the retina, forming a relativelydark central blood column with lighter edges, the intensityfalling off towards the background retinal intensity. In addi-tion, a fraction of the light is absorbed by the vessel wall.If the image intensity is graphed along a profile line cuttingacross the vessel, kick points are sometimes visible [4]; seeFigure 1. These slanting shoulders on the profile correspond-ing to the vessel wall are visible on high resolution and well-focused images, but not usually on low-resolution or blurredimages, or for small vessels [2]. The distance between themis described by [4] as an accurate vessel diameter estimatorthat can be measured. He reported that the kick point dis-tance is more accurate than that provided by the (automatic)Full Width Half Maximum algorithm, which was proposedby [5]. On the other hand, [6] and [7] report that the appar-ent diameter of the blood column is a reasonable estimator ofthe real intra-vascular width, even when the vessel wall is notvisible.In [1], we introduced a manual edge marking technique,EPMT, where a specially-designed tool is used to click alongthe vessel edges. An algorithm, described below, is subse-quently used to determine the profile direction, and interpo-lates between click points to determine the width. This ap-proach was used to provide the ground truth in [8].This paper compares KPMT and EPMT. Section II.de-scribes the data set used, section III.gives more details on thealgorithms, and describes how they were compared; sectionIV.gives the results of the comparison, and section V.concludesthe paper.II. MATERIALSImages were selected by a consultant ophthalmologistfrom the fundus image database of the diabetic retinopathyFig. 1: An Illustration of a vessel cross-profile. The width may be definedas the distance between kick points.clinic at Sunderland Eye Infirmary. The image set consists of164 ground truth widths obtained from two high-resolutionfundus images with a 60 degree field of view, and pho-tographed using a Canon 60uv fundus camera. All 164 vesselwidths were selected from large diameter non-tortuous vesselsegments between bifurcations. The dimensions of the high-resolution images were 3300× 2600 pixels. Figure 2 showssamples from the data set. The mark-up is time consuming,so only a few segments could be used; we have concentratedon clear, high-resolution images so that this preliminary studyis carried out under ideal conditions. The image set and kick-point widths have previously been used to provide the groundtruth measurements in [8]. Vessel centre lines and profile di-rections were determined by the algorithm described in [1].Fig. 2: Marked segments in the kick point image set.III. METHODSA. The Kick Point Marking MethodFor KPMT, the users were presented with intensity profilesconstructed by bilinear interpolation along the defined profilelines. They used a specially-developed software tool to markthe kick-points, or to estimate their position when not visible.B. The Edge Point Marking MethodThe EPMT technique uses a specially developed interac-tive mark-up tool. Starting from one end of a segment the ob-server chooses an edge and nominates edge points by clickingwith the mouse until the other end of the segment is reached.The observer then returns back to the starting segment end,and similarly marks up the other edge; see Figure 3. The ac-curacy of this method depends on the discretization (the dis-tance between two following points) of edge points. The toolallows the user to zoom up to super-pixel levels (in whichcase each pixel is drawn as a square), and then to nomi-nate points at sub-pixel level if desired. A cubic spline is fitthrough the edge points, and regularly sampled: the resultingpoints are not discretized to pixel centers. EPMT is thereforeable to extract widths to sub-pixel accuracy if the user canperceive such.Fig. 3: EPMT marking tool. The approximate vessel centerline is displayedto show the observer which segment is to be marked.The edge point sampled from the splines are used to con-struct a series of profiles and width measurement. The endpoints of the two edges are not necessarily located alonga single profile line, so any unnecessary end sections aretrimmed. The algorithm has four steps:1. A cubic spline is fit through the user-nominated edgepoints, and regularly sampled (at spacing 0.2 pixels).2. Choosing a point on one side as P1, the nearest edge pointon the other side is found, and labelled P2. Then, the near-est point to P2 on the same side as P1 is located and la-belled; see figure 4(a). The point P3 is often, but not al-ways, the same as point P1.Fig. 5: Extracting vessel diameters in EPMT.3. The local segment direction (LSD) is calculated as themean of the perpendicular vectors on vectors ~P2P1 and~P2P3; see figure 4(b).4. The vectors between P2 and a set of edge points from theother side, including all the points between P1 and P3 arecalculated. The point P4 from that set with a minimumdeviation from pi/2 is defined; see figure 4(c).5. The point P4 is shifted along a B-spline fitted to the edgepoints, to lie on a perpendicular profile with local seg-ment direction (LSD); see figure 4(d). The distance be-tween point P2 and shifted P4 is the local diameter.Figure 5 shows an example of EPMT in operation.C. Experimental ApproachThe measurements for each technique were repeated bythree observers (O1, O2 and O3). We are interested in two is-sues. First, to what extent can different observers reliably pro-duce the same results for a particular profile? We characterizethis by observing the difference in the mean measurementsbetween the observers. Second, given that there may arguablybe different individual perceptions of the edge position (andthere is no absolute definition of what constitutes the edge), towhat extent can an individual observer reliably mark along avessel? We characterize this by calculating the mean observerestimate (O¯) for each methods, and then the differences be-tween the mean and individual observers. If a technique isprone to observer bias (consistent mis-estimation), the ob-server means will be dissimilar. If a technique is prone tovariance, the variance of the differences will be large even ifthe means are close together.The KPMT technique requires a profile direction to benominated before the width can be calculated, whereasEPMT defines the profile direction. To allow comparison ofthe techniques without biasing the results in favour of either,we used a ground truth profile direction defined by the tech-Fig. 4: Extracting width from EPMT marking: (a) shortest distances fromboth edges are calculated to provide two or three edge points; (b) directionvectors at edge points and the local segment direction (LSD); (c) theperpendicular direction to the LSD where point P4 should be located; (d) P2and P4 form a perpendicular profile with the local segment direction,located on the tangent of the largest circle inside the segment.nique presented in [1]. The KPMT measurement is then takendirectly along this profile direction, whereas the EPMT mea-surement is taken from the EPMT profile with its centre pointnearest to the profile centre point, (EPMT profiles are con-structed at 0.2 pixel centre point spacing). This method al-lows us to examine the relative performance of the methodswith respect to edge position, although the EPMT method isslightly disadvantaged as observers may produce slightly dif-ferent profile directions in addition to edge positions.IV. RESULTSThe descriptive statistics of KPMT and EPMT are summa-rized in Table 1 and Table 2 respectively.Mean StdDStdE95% Conf I Min MaxLowerBoundUpperBoundGT 7.40 0.36 0.03 7.34 7.45 6.41 8.38O1 7.74 0.63 0.05 7.64 7.84 5.49 9.10O2 7.29 0.49 0.04 7.21 7.36 6.07 7.94O3 7.17 0.37 0.03 7.11 7.23 6.21 8.22Table 1: Descriptive statistics for KPMT.Human observers are subjective and prone to inter-observer and intra-observer variability [3]. Thus a more ro-bust approach for generating ground truth is to combine mul-tiple human generated manual segmentations, even thoughthe process is more costly, and there may be some uncertaintyamong observers. Tables 1 and 2 show that there was a greaterspread in the mean measurements for EPMT than for KPMT.Table 3 gives the standard deviations of the differences be-tween the observers and the observer mean measurements.Mean StdDStdE95% Conf I Min MaxLowerBoundUpperBoundGT 7.52 0.42 0.03 7.46 7.59 6.33 8.42O1 7.00 0.52 0.04 6.91 7.08 5.51 8.50O2 7.60 0.42 0.03 7.54 7.67 6.23 8.82O3 7.97 0.47 0.04 7.90 8.05 6.66 9.16Table 2: Descriptive statistics for EPMT.KPMT EPMTDiff SD Diff SDO1 0.417 0.234O2 0.317 0.213O3 0.326 0.233Table 3: Standard deviation of observer measurement differences inKPMT and EPMT.The EPMT technique is more precise than KPMT, witha difference standard deviation of approximately 0.23 over-all, in comparison to 0.35 for KPMT. This superior preci-sion occurs despite the inherent disadvantage for EPMT inthe evaluation technique, since EPMT measurements may beeffected by variations in estimated profile direction. This vari-ance shows that the observers had difficulty applying the kickpoint method consistently and accurately.EPMT has a number of advantages compared to KPMT:the user marks the original image, not a 1D profile con-structed by interpolation from the image; it automatically de-termines the direction of the profile line; and the vessel edgesare always visible. It has one clear disadvantage: there is noabsolute definition of the vessel edge, and the observer has todetermine where the edge lies using his or her own judge-ment, bearing in mind that in fact the intensity slopes offgradually at a vessel edge and so user perception of the edgemay well vary.V. CONCLUSIONWe have conducted a preliminary comparison of two tech-niques to support the manual measurement of retinal vesselwidths. Such techniques are useful in providing ground truthmeasurements for automated measurement algorithms, andfor studies relating retinal vascular geometry to diseases.The evaluation suggests that the EPMT technique, whichrelies on interpolating between edge points marked on azoomed-up image, is more precise, but more subject to in-dividual perceptual bias, than the kick-point marking ap-proach. The comparison has been conducted with a fairlysmall database containing clear, high resolution images, andso the conclusions are necessarily preliminary. As we knowthat kick-points are only visible under ideal conditions, wespeculate that EPMT is likely to have a more marked advan-tage when evaluated under more challenging conditions.In future work we will evaluate the techniques against abroader range of images, including those presenting patholo-gies. We will also extend the evaluation to consider the ef-fect of the identification of the profile direction, in additionto edge position.VI. ACKNOWLEDGEMENTSThe authors gratefully acknowledge the contribution ofSunderland Eye Infirmary and the observers.REFERENCES1. Al-Diri Bashir, Hunter Andrew, Steel David, Habib Maged, HudaibTaghread, Berry Simon. REVIEW - A Reference Data Set for Reti-nal Vessel Profiles in The 30th Annual International Conference of theIEEE Engineering in Medicine and Biology Society in Vancouver(BritishColumbia, Canada) 2008.2. Lowell James A., Hunter Andrew, Steel David, Basu Ansu, RyderRobert, Kennedy R. Lee. Measurement of Retinal Vessel Widths fromFundus Images Based on 2-D Modeling IEEE transactions on medicalimaging. 2004;23:1196-1204.3. Suri Jasjit S., Laxminarayan Swamy. Angiography And Plaque Imaging:Advanced Segmentation Techniques. CRC Presssecond ed. 2003.4. Rassam Salwan M. B., Patel Vinod, Brinchmann-Hansen Olaf, EngvoldOddbjorn, Kohner Eva M.. Accurate Vessel Width Measurement FromFundus Photographs: A New Concept British Journal of Ophthalmology.1994;78:24-29.5. Brinchmann-Hansen Olaf, Heier Halvor. Theoretical Relations BetweenLight Streak Characteristics And Optical Properties Of Retinal VesselsActa Ophthalmologica, supplement. 1986;179:33-37.6. Brinchmann-Hansen Olaf, Engvold Oddbjorn. Microphotometry Of TheBlood Column and The Light Streak On Retinal Vessels In Fundus Pho-tographs Acta Ophthalmologica, supplement. 1986;179:9-19.7. Brinchmann-Hansen Olaf, Heier Halvor. The Apparent And True WidthOf The Blood Column In Retinal Vessels Acta Ophthalmologica, sup-plement. 1986;179:29-32.8. Al-Diri Bashir, Hunter Andrew. An Active Contour Model for Segment-ing and Measuring Retinal Vessels IEEE Transactions on Medical Imag-ing. 2009;28:1488-1497. Epub 2009 Mar 24.Author: Bashir Al-DiriInstitute: The University of LincolnStreet: BrayfordCity: LincolnCountry: UKEmail: baldiri@lincoln.ac.uk

An Active Contour Model for Segmenting and Measuring Retinal Vessels

Angiography And Plaque Imaging: Advanced Segmentation Techniques.

Brinchmann-Hansen Olaf, Engvold Oddbjorn, Kohner Eva M.. Accurate Vessel Width Measurement From Fundus Photographs: A New Concept British Journal of Ophthalmology.

Engvold Oddbjorn. Microphotometry Of The Blood Column and The Light Streak On Retinal Vessels In Fundus Photographs Acta Ophthalmologica,

Heier Halvor. The Apparent And True Width Of The Blood Column

Heier Halvor. Theoretical Relations Between Light Streak Characteristics And Optical Properties Of Retinal Vessels Acta Ophthalmologica,

Hudaib Taghread, Berry Simon. REVIEW - A Reference Data Set for Retinal Vessel Proﬁles

Accurate methods for manually marking retinal vessel widths

Accurate methods for manually marking retinal vessel widths

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