Wadim Wojciechowski

Application of shape description methodology to hand radiographs interpretation

In this paper, a shape description methodology, introduced by Jakubowski [6] is applied to hand radiographs interpretation, in order to recognize bones borders shapes in the fingers regions. It is shown that the classical approach can be used only for preliminary analysis. Therefore, the improved method, based on fuzzy approach, is considered.

Identifying the borders of the upper and lower metacarpophalangeal joint surfaces on hand radiographs

In this paper, the next stage of out studies concerning the computer analysis of hand X-ray digital images is described. An algorithm identifying the borders of the upper and lower joint surfaces on hand radiographs is proposed. It is based on local segmentation and profile plots analysis. The described algorithm achieved high efficiency -mean distance distribution signature for complete borders was equal to 0.118mm. Therefore, it can be applied both to trace development of hand joints diseases and analysis of bone contour shapes using syntactic methods.

Modified jakubowski shape transducer for detecting osteophytes and erosions in finger joints

In this paper, a syntactic method of pattern recognition is applied to hand radiographs interpretation, in order to recognize erosions and osteophytes in the finger joints. It is shown that, the classical Jakubowski transducer does not distinguish contours of healthy bones from contours of affected bones. Therefore, the modifications of the transducer are introduced. It is demonstrated, that the modified transducer correctly recognizes the classes of bone shapes obtained based on the medical classification: healthy bone class, erosion bone class and osteophyte bone class.

Computer aided erosions and osteophytes detection based on hand radiographs

In this paper we present a computer system to detect erosions and osteophytes from hand radiographs, the most common symptoms of rheumatic diseases. The designed, implemented and verified algorithm uses techniques of image processing, image analysis and pattern recognition. In the stages of image processing and image analysis, the locations of metacarpal bones, the outlines of finger bones, the locations and outlines of joints and finally the borders of joint surfaces are identified. In the pattern recognition stage, a shape description language is used for each border of the joint surface to detect the locations of erosions and osteophytes on hand radiographs. The presented algorithm expands on those known from the literature, because besides erosions it also detects osteophytes. Moreover, in contrast to previous systems, it analyses proximal interphalangeal joints and distal interphalangeal joints. The obtained results are satisfactory and very promising. The joints are successfully located in 98.3% of cases. The average mean distance between the borders pointed out by radiologists and obtained from the system varies between 0.094mm and 0.157mm, while the sensitivity and the specificity equal around 70% in most of the cases. Therefore, it can become a basis for the diagnosis of certain diseases. Graphical abstractDisplay Omitted HighlightsWe introduce a new algorithm of local segmentation based on a region growing.We define a new shape description language for syntactic pattern recognition.We present a multi-stage algorithm, which expands on those created so far.We designed, implemented and tested an automatic computer system which detects erosions and osteophytes (the system operator has to only load the image and mark the area of the analysis).

Improved fuzzy entropy algorithm for x-ray pictures preprocessing

The fuzzy entropy algorithm was designed for preprocessing of photos taken in the visible spectrum of light. However it did not produce satisfying results when it is directly applied to X-ray pictures. In this paper we present significant improvements of this approach and apply it to hand radiographs. The noise elimination and the bone contourisation is the task which is studied in this paper. Not only is the algorithm modified but also it is combined with using of median and minimum filters. The presented approach allows us to obtain satisfying noise elimination and clear bone contourisation.

Fast automated segmentation of wrist bones in magnetic resonance images

PURPOSE According to current recommendations in diagnostics of rheumatoid arthritis (RA), Magnetic resonance (MR) images of wrist joints are used to evaluate three main signs of RA: synovitis, bone edema and bone erosions. In this paper we present an efficient method for segmentation of 15 bones present on MR images of the wrist which is inevitable for future computer-assisted diagnosis system for RA lesions. METHOD The segmentation procedure consists of two stages. The first stage is evaluation of markers (parts of bones working as seeds for the watershed algorithm) for bones in every joint: the distal parts of ulna and radius, the proximal parts of metacarpal bones and carpal bones. In the second stage the watershed from markers algorithm is applied based on the markers determined in the previous stage and the wrist bones are segmented. The markers were found using Multi Otsu algorithm along with custom method for filtering bones from other tissues. RESULTS We analyzed 34 MR images. The automated segmentations were compared with manual segmentations using metrics: accuracy ACC derived from area under ROC curve AUC, Dice coefficient and mean absolute distance MAD. The mean (standard deviation) values of ACC, Dice and MAD were 0.99 (0.02), 0.98 (0.04) and 1.21 (0.39), respectively. CONCLUSION The results of this study prove that our method is efficient and gives satisfactory results for segmentation of bones on low-field MR images of the wrist.

A Shape Description Language for Osteophytes Detection in Upper Surfaces of the Metacarpophalangeal Joints

In this paper, the successive module of the computer system for hand diseases diagnosis support is presented. Based on the upper surface borders of the metacarpophalangeal joints, syntactic description is constructed. Then, it is analysed to verify if considered border contains osteophytes. As has been presented, shape description introduced in this paper can be used to distinguish contour of the upper surface with and without osteophytes. This kind of diversification is required to build an intelligent system for joint diseases diagnosis.

Mechatronics supported virtual bronchoscopy for navigation in bronchoscopy of peripheral respiratory tree

The purpose of this paper is to test conjecture that the data related to manual maneuvers with the handle of a catheter of a bronchoscope provides information sufficient for accomplishing the task of estimating the position, orientation and flexure of the distal end of a catheter. To test the conjecture three devices were developed and mounted on the handle of a catheter and on the external opening of the working channel of a bronchoscope. The devices recorded shifts of a catheter, rotations of the catheter handle and the shifts of the ring of the catheter, directly related to the flexure of the tip of the catheter. In laboratory experiments it has been shown that the shift of the catheter can be monitored with accuracy of 2 mm and the catheter tip rotation and flexure angles can be monitored with accuracy of 10 and 20°, respectively. The accuracy of the developed devices compares favorably with the accuracy of the current standard methods for supporting peripheral bronchoscopy.

Automated Assessment of Hallux Valgus in Radiographic Images

The purpose of the study was to develop an automated method for measurement of the selected angular variables, characterizing foot skeleton based on dorsoplantar projection radiographs. The study was a retrospective analysis of radiographic data. Totally, 50 dorsoplantar projection radiographs of a weight-wearing foot were analyzed (24 left and 26 right feet) of 32 patients (23 female, 9 male). Various quantities were measured to assess the severity of hallux valgus. The measurements were performed manually and with an automated method designed in the study. The automated and manual measurements were correlated. Repeated manual measurements were additionally performed to determine the variability of manual assessment of the hallux valgus. High correlation between manual and automated measurements have been observed. The accuracy of the framework is comparable with the accuracy of manual measurements.

Automated assessment of synovitis in 0.2T magnetic resonance images of the wrist

According to the current recommendations in diagnosis of rheumatoid arthritis (RA), Magnetic Resonance (MR) images of wrist joints are used to evaluate three main types of lesions: synovitis, bone edema and bone erosions. In the clinical practice, the RA-related lesions seen in MR images are assessed manually with the semi-quantitative RAMRIS scoring system. In this paper we present an automated method for inflamed synovial membrane volume determination, based on the analysis of pre- and post-contrast MR images and segmentation of wrist bones seen in MR images. We found that the correlation between the automatically quantified volume of synovitis and RAMRIS scores was in the range from 0.76 to 0.87 for the total RAMRIS synovitis score. This can be compared with the correlation between the manually quantified volume of synovitis and RAMRIS scores which was in the range from 0.75 to 0.81 for the total synovitis score. The results of the study demonstrate that computer assisted methods for assessment of synovitis have great potential for clinical applications.