The knee is the most affected joint in children with cerebral palsy. Flexion contracture of the k... more The knee is the most affected joint in children with cerebral palsy. Flexion contracture of the knee is the cause of the crouch gait pattern, instability in stance phase of gait, and difficulties during standing and sitting, and other daily living activities. Hip flexion contracture in crouch gait is mostly com-pensation of the knee flexion contracture and ankle equines. The psoas muscle is the primary reason for the hip flexion contracture and is known to be associated with increased anterior pelvic tilt, crouching gait, hip instability and lumbar lordosis. Children with cerebral palsy may even give up walking due to the high energy demand in the adult period. The purpose of this article is to review the causes of the knee and hip flexion contractures, clinical evaluations, and treatment principles in children with cerebral palsy. The biomechanical reasons of knee and hip flexion deformity are discussed in detail in the light of previous studies and gait analysis data. (JAREM 2012;...
This paper introduces a study of automatic femoral head detection in magnetic resonance imaging (... more This paper introduces a study of automatic femoral head detection in magnetic resonance imaging (MRI) data sequences. For the 3D detection of the multiform femoral heads having both spheric and aspheric shape structures, the threedimensional form of the Integro-differential Operator (IDO) was performed. Following a set of image pre-processing operations including image intensity normalization, histogram equalization, morphological correction, hip joint separation and image binarization performed on bilateral hip MRI data sequences, the hip joints images are obtained in binary form in 3D. Then, the 3D form of IDO is performed in a predefined image volume to detect the femoral heads. Within the experimental studies performed on 8 bilateral hip MRI data sequences belonging to 6 LeggCalve-Perthes disease (LCPD) patients, promising success rates were observed. In detection of a total of 16 femoral heads, 8 of which are spheric and 8 of which are aspheric, 0.7021 (± 0.3160) and 0.6757 (± 0.2989) DSC values measured for the spheric and aspheric femoral heads, respectively.
2018 26th Signal Processing and Communications Applications Conference (SIU), 2018
In this paper, we present a study on automatic detection of center coordinate and radius of femor... more In this paper, we present a study on automatic detection of center coordinate and radius of femoral heads in coronal MR slices belong to the patients with Legg-Calve-Perthes (LCP) disease. LCP which lead to dysfunction caused by the deformity of the spherical structure of the femoral head in hip joint is a hip disorder in pediatric orthopaedics. Especially in segmentation studies, automatic detection of femoral head is an important issue in the assessment and quantification studies of the hip diseases. So that, we aimed to detect the healthy and pathological femoral heads in MR slices of LCP patients by using the Circular Hough Transform (CHT) in this study. In this context, first the MR sections are divided vertically into two equal halves to separate the hip joints and then edge images are obtained by using Canny's edge detection method. Finally, femoral heads are detected by performing the CHT on edge images. Successful results were achieved in experiments on healthy and path...
2018 Medical Technologies National Congress (TIPTEKNO), 2018
In this paper, various medical software tools, which have been developed for the manual, semi-aut... more In this paper, various medical software tools, which have been developed for the manual, semi-automatic or fully-automatic segmentation of magnetic resonance (MR) images, and some features of these software tools are presented and discussed. MR imaging is one of the medical imaging modalities which are frequently preferred by the clinicians and surgeons. Segmentation of the MR images in clinical researches and in clinical engineering-based studies is emerging as a considerable requirement for the analysis of the disease images and the diseases. Medical software tools have been developed to meet this need and to provide facilities for the clinicians, surgeons and researchers in computer-aided research projects they conduct. Currently available MR image segmentation tools have many differences when considering criteria such as design, graphical-user interface and functions they provide. In this short review study, we briefly summarized 10 different MR image segmentation software tools...
2021 29th Signal Processing and Communications Applications Conference (SIU)
This paper presents a study on evaluation of the point sets obtained via Random Point Sub-samplin... more This paper presents a study on evaluation of the point sets obtained via Random Point Sub-sampling (RPS) in rigid registration of 2-dimensional (2D) proximal femur surfaces. In the first stage of the proposed study, the edges of the proximal femurs, which were manually segmented from bilateral hip magnetic resonance (MR) images, were extracted and the surface information of these proximal femurs was obtained as point clouds. In the further stages, the sizes of the existing point clouds were reduced by performing RPS on point clouds describing the proximal femurs, and the right and left proximal femurs were registered rigidly with the Iterative Closest Point (ICP) method. In this way, it was aimed to register the proximal femur surfaces faster and more successfully over a small number of points. In performance evaluations performed on 13 hip MR images of 13 patients diagnosed with Legg-Calve-Perthes (LCP) disease, it was ensured that proximal femur surfaces were successfully registered faster than the normal case by using the points obtained via RPS. The proposed approach can be applied to different problems such as shape quantification and shape modelling/matching of proximal femurs. Furthermore, it is also promising for the realtime clinical applications in the related fields.
Pediatric long bones have some different characteristics including thicker periosteum, better blo... more Pediatric long bones have some different characteristics including thicker periosteum, better blood supply, shorter healing time, and higher remodeling capacity than the adult bone. Therefore, most fractures are treated conservatively with traction or casting. However, the prolongation of the treatment can cause “casting disease,” which manifests as joint stiffness, muscle weakness, and disuse osteopenia [1]. Prolonged treatment also prevents parents from working and children from going to school. The cost of treatment with external fixation is lower than treatment with traction in hospital and hospital/home (Hedin 2004).
Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing
This paper presents a study of 3D femoral head detection in coronal magnetic resonance (MR) imagi... more This paper presents a study of 3D femoral head detection in coronal magnetic resonance (MR) imaging sequences to detect the spheric and aspheric femoral heads using the Spherical Hough Transform (SHT). Shape structure and functionality of the femoral head can be affected by a wide range of hip disorders. In most of the computerized analysis and assessment cases of the hip joint, segmentation of the proximal femur and femoral head is performed on the image sequences that are provided by the several medical imaging modalities. Determination of initial points, detection of the tissue boundaries and segmentation of the tissues are important challenges in automatic or semi-automatic proximal femur segmentation methods. In this paper, we aimed to perform a preliminary study based on 3D femoral head detection in bilateral MR hip images in coronal plane of patients with Legg-Calve-Perthes disease (LCPD). Firstly, MR sections are divided vertically into two equal halves automatically to separate the healthy and pathological hip joints and then Canny's edge detection method is performed to obtain edge images. Finally, 3D SHT is performed to detect the spherical structure of femoral heads. Automatic detection of the femoral head with SHT provides a starting point for the segmentation of the femoral head ball and proximal femur. Furthermore, it also allows for 3D segmentation of the femoral head sphere with the radius information that it provides with the 3D sphere center coordinates. Performance evaluations and experimental results observed on 8 bilateral MR imaging sequences belong to 6 subjects show that proposed method has promising results.
2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)
By various hip joint disorders, human proximal femurs are deformed and the natural pure shape of ... more By various hip joint disorders, human proximal femurs are deformed and the natural pure shape of the human proximal femurs is lost. Automatic classification of the proximal femur deformities emerging as a result of the hip diseases is important for the computer-aided diagnosis. In this paper, a study on automatic classification of Waldenstrom stages of Legg-Calve-Perthes disease (LCPD) patients from the 2D total deformity occurring on the proximal femurs is presented. Within the scope of the study, total deformities of the pathological proximal femurs were quantified initially by using a novel and hip joint symmetry based method that we reported in our previous research studies. To this end, total deformities of the pathological proximal femurs were represented as rational values. To classify the Waldenstrom stages of LCPD automatically, the Support Vector Machine (SVM) classifier was employed. Within the experimental studies performed on a dataset consisting of 13 magnetic resonance (MR) images of 13 patients with LCPD, an accuracy about 62% was observed in automatic classification of the Waldenstrom stages of the LCPD patients. The main contribution of the paper is that it is the first study so far, to the best of our knowledge, for the computer vision and machine learning based automatic classification of Waldenstrom stages of LCPD.
The knee is the most affected joint in children with cerebral palsy. Flexion contracture of the k... more The knee is the most affected joint in children with cerebral palsy. Flexion contracture of the knee is the cause of the crouch gait pattern, instability in stance phase of gait, and difficulties during standing and sitting, and other daily living activities. Hip flexion contracture in crouch gait is mostly com-pensation of the knee flexion contracture and ankle equines. The psoas muscle is the primary reason for the hip flexion contracture and is known to be associated with increased anterior pelvic tilt, crouching gait, hip instability and lumbar lordosis. Children with cerebral palsy may even give up walking due to the high energy demand in the adult period. The purpose of this article is to review the causes of the knee and hip flexion contractures, clinical evaluations, and treatment principles in children with cerebral palsy. The biomechanical reasons of knee and hip flexion deformity are discussed in detail in the light of previous studies and gait analysis data. (JAREM 2012;...
This paper introduces a study of automatic femoral head detection in magnetic resonance imaging (... more This paper introduces a study of automatic femoral head detection in magnetic resonance imaging (MRI) data sequences. For the 3D detection of the multiform femoral heads having both spheric and aspheric shape structures, the threedimensional form of the Integro-differential Operator (IDO) was performed. Following a set of image pre-processing operations including image intensity normalization, histogram equalization, morphological correction, hip joint separation and image binarization performed on bilateral hip MRI data sequences, the hip joints images are obtained in binary form in 3D. Then, the 3D form of IDO is performed in a predefined image volume to detect the femoral heads. Within the experimental studies performed on 8 bilateral hip MRI data sequences belonging to 6 LeggCalve-Perthes disease (LCPD) patients, promising success rates were observed. In detection of a total of 16 femoral heads, 8 of which are spheric and 8 of which are aspheric, 0.7021 (± 0.3160) and 0.6757 (± 0.2989) DSC values measured for the spheric and aspheric femoral heads, respectively.
2018 26th Signal Processing and Communications Applications Conference (SIU), 2018
In this paper, we present a study on automatic detection of center coordinate and radius of femor... more In this paper, we present a study on automatic detection of center coordinate and radius of femoral heads in coronal MR slices belong to the patients with Legg-Calve-Perthes (LCP) disease. LCP which lead to dysfunction caused by the deformity of the spherical structure of the femoral head in hip joint is a hip disorder in pediatric orthopaedics. Especially in segmentation studies, automatic detection of femoral head is an important issue in the assessment and quantification studies of the hip diseases. So that, we aimed to detect the healthy and pathological femoral heads in MR slices of LCP patients by using the Circular Hough Transform (CHT) in this study. In this context, first the MR sections are divided vertically into two equal halves to separate the hip joints and then edge images are obtained by using Canny's edge detection method. Finally, femoral heads are detected by performing the CHT on edge images. Successful results were achieved in experiments on healthy and path...
2018 Medical Technologies National Congress (TIPTEKNO), 2018
In this paper, various medical software tools, which have been developed for the manual, semi-aut... more In this paper, various medical software tools, which have been developed for the manual, semi-automatic or fully-automatic segmentation of magnetic resonance (MR) images, and some features of these software tools are presented and discussed. MR imaging is one of the medical imaging modalities which are frequently preferred by the clinicians and surgeons. Segmentation of the MR images in clinical researches and in clinical engineering-based studies is emerging as a considerable requirement for the analysis of the disease images and the diseases. Medical software tools have been developed to meet this need and to provide facilities for the clinicians, surgeons and researchers in computer-aided research projects they conduct. Currently available MR image segmentation tools have many differences when considering criteria such as design, graphical-user interface and functions they provide. In this short review study, we briefly summarized 10 different MR image segmentation software tools...
2021 29th Signal Processing and Communications Applications Conference (SIU)
This paper presents a study on evaluation of the point sets obtained via Random Point Sub-samplin... more This paper presents a study on evaluation of the point sets obtained via Random Point Sub-sampling (RPS) in rigid registration of 2-dimensional (2D) proximal femur surfaces. In the first stage of the proposed study, the edges of the proximal femurs, which were manually segmented from bilateral hip magnetic resonance (MR) images, were extracted and the surface information of these proximal femurs was obtained as point clouds. In the further stages, the sizes of the existing point clouds were reduced by performing RPS on point clouds describing the proximal femurs, and the right and left proximal femurs were registered rigidly with the Iterative Closest Point (ICP) method. In this way, it was aimed to register the proximal femur surfaces faster and more successfully over a small number of points. In performance evaluations performed on 13 hip MR images of 13 patients diagnosed with Legg-Calve-Perthes (LCP) disease, it was ensured that proximal femur surfaces were successfully registered faster than the normal case by using the points obtained via RPS. The proposed approach can be applied to different problems such as shape quantification and shape modelling/matching of proximal femurs. Furthermore, it is also promising for the realtime clinical applications in the related fields.
Pediatric long bones have some different characteristics including thicker periosteum, better blo... more Pediatric long bones have some different characteristics including thicker periosteum, better blood supply, shorter healing time, and higher remodeling capacity than the adult bone. Therefore, most fractures are treated conservatively with traction or casting. However, the prolongation of the treatment can cause “casting disease,” which manifests as joint stiffness, muscle weakness, and disuse osteopenia [1]. Prolonged treatment also prevents parents from working and children from going to school. The cost of treatment with external fixation is lower than treatment with traction in hospital and hospital/home (Hedin 2004).
Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing
This paper presents a study of 3D femoral head detection in coronal magnetic resonance (MR) imagi... more This paper presents a study of 3D femoral head detection in coronal magnetic resonance (MR) imaging sequences to detect the spheric and aspheric femoral heads using the Spherical Hough Transform (SHT). Shape structure and functionality of the femoral head can be affected by a wide range of hip disorders. In most of the computerized analysis and assessment cases of the hip joint, segmentation of the proximal femur and femoral head is performed on the image sequences that are provided by the several medical imaging modalities. Determination of initial points, detection of the tissue boundaries and segmentation of the tissues are important challenges in automatic or semi-automatic proximal femur segmentation methods. In this paper, we aimed to perform a preliminary study based on 3D femoral head detection in bilateral MR hip images in coronal plane of patients with Legg-Calve-Perthes disease (LCPD). Firstly, MR sections are divided vertically into two equal halves automatically to separate the healthy and pathological hip joints and then Canny's edge detection method is performed to obtain edge images. Finally, 3D SHT is performed to detect the spherical structure of femoral heads. Automatic detection of the femoral head with SHT provides a starting point for the segmentation of the femoral head ball and proximal femur. Furthermore, it also allows for 3D segmentation of the femoral head sphere with the radius information that it provides with the 3D sphere center coordinates. Performance evaluations and experimental results observed on 8 bilateral MR imaging sequences belong to 6 subjects show that proposed method has promising results.
2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)
By various hip joint disorders, human proximal femurs are deformed and the natural pure shape of ... more By various hip joint disorders, human proximal femurs are deformed and the natural pure shape of the human proximal femurs is lost. Automatic classification of the proximal femur deformities emerging as a result of the hip diseases is important for the computer-aided diagnosis. In this paper, a study on automatic classification of Waldenstrom stages of Legg-Calve-Perthes disease (LCPD) patients from the 2D total deformity occurring on the proximal femurs is presented. Within the scope of the study, total deformities of the pathological proximal femurs were quantified initially by using a novel and hip joint symmetry based method that we reported in our previous research studies. To this end, total deformities of the pathological proximal femurs were represented as rational values. To classify the Waldenstrom stages of LCPD automatically, the Support Vector Machine (SVM) classifier was employed. Within the experimental studies performed on a dataset consisting of 13 magnetic resonance (MR) images of 13 patients with LCPD, an accuracy about 62% was observed in automatic classification of the Waldenstrom stages of the LCPD patients. The main contribution of the paper is that it is the first study so far, to the best of our knowledge, for the computer vision and machine learning based automatic classification of Waldenstrom stages of LCPD.
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