Jan Juszczyk

Granular computing in model based abdominal organs detection

Detection of region specific voxel is a true challenge in many segmentation procedures. In this study a concept of implementing granular computing in the detection of anatomical structures in abdominal computed tomography (CT) scans is introduced. After proving the usefulness of the information granules to identify voxels that mark certain organs, an automatic model-based approach has been developed. A three-parameter granule that combines the interval and density distribution of voxels has been introduced and employed to identify organ specific voxels of the liver, spleen and kidneys. The specificity of the information granules varies between 90 and 99% for the liver and spleen and over 85% for the kidneys.

Radiological Atlas for Patient Specific Model Generation

The paper presents the development of a radiological atlas employed in an abdomen patient specific model verification.

Image Navigation in Minimally Invasive Surgery

This study presents the development of an image navigation system dedicated to assist a miniinvasive abdominal surgery. First, the system overview is discussed. Then, a development of a mesh model of abdominal structure is presented. Next, a system calibration including the component as well as patient registration is described.The evaluation of the system has been performed separately for each component. The accuracy of calibration as well as patient registration is reported. This yields the robustnes evaluation of the overall system.

Shape and function of the diaphysis of the human tibia

There is an agreement about the principle that bones are optimized to resist daily loads. This has never been ascertained for the human tibia. One of the main load components in the tibia in vivo is a cantilever load (with a linearly varying bending moment, with its largest component in the sagittal plane). investigated if the cross-section of the diaphysis and its variation along the tibia make it an optimized structure with respect to such loads. Six cadaveric tibias were CT-scanned. The geometry and material properties were extracted from the CT-scans, and analyzed along the tibias. A linear variation along the tibia was found for the second moments of area and inertia, and the section modulus in the sagittal plane (slightly less linear in the frontal plane). Conversely, the other properties (polar moments and cross-section are) were much less linear. This suggests that the structure is optimized to resist a bending moment that varies linearly along the tibia. The tibias were instrumented with 28 triaxial straingauges each. Strain was measured under cantilever loading in the sagittal and frontal planes, under quasi-constant-bending in the sagittal and frontal planes, under torsional loading, and with an axial force. The strain distribution was remarkably uniform when cantilever loading was applied in the sagittal plane and slightly less uniform when cantilever loading was applied in the frontal plane. Strain variations were one order of magnitude larger for all other loading configurations. This shows that the tibia is a uniform-stress structure (i.e. optimized) for cantilever loading.

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.

Purpose A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. Methods We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. Results The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. Conclusion The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

ToF-Data-Based Modelling of Skin Surface Deformation

Nowadays, the imaging techniques followed by advanced image processing algorithms become an indispensable part of diagnostic and surgical procedures. During recent years, an increasing demand for intra-surgical modalities can be noticed. The work aims at modelling the deformation of human skin surface caused by a navigated stick based on the point cloud acquired by a Time-of-Flight (ToF) camera. The data acquired by ToF and optical tracker are synchronized. Then, the skin deformation is modelled by applying a physics engine. The model evaluation is based on a Hausdorff distance. The results prove the applicability of the developed workflow.

Biopsy Needle and Tissue Deformations Detection in Elastography Supported Ultrasound

During last decades a fast development of imaging techniques has offered the intra-operative visualization as the integral part of surgical tools. For this, the automated and robust analysis of ultrasound images is required. The paper meets these requirements targeting in detection of tissue deformations caused by biopsy needle inserted in the body. The presented novel technique uses ultrasound data supported by elastography images. In the feature set, the automated detection algorithm introduces Histogram of Oriented Gradients and image entropy. The further classification steps applies Weighted Fuzzy C-Means (WFCM) clustering technique resulting in deformation detection sensitivity and specificity at levels 0.793 and 0.94, respectively.

Patient Specific Phantom in bimodal image navigation system.

The paper presents the multistep methodology of bimodal Patient Specific Phantom (PSP) development. First, CT based abdominal digital model is designed. It serves as a source for designing organ moulds manufactured by means of a 3D-printer. The collagen based colloid fills the moulds yielding the organ casts. The PSP permits a bimodal navigation system to be developed that employs a realistic CT-based digital model and US imaging. Highly accurate results were achieved with mean Dice similarity coefficient value of 0.92 and Hausdorff distance 9.67 mm.

Breast Cancer Segmentation Method in Ultrasound Images

The most common type of cancer among women is breast cancer. The early diagnosis is crucial in a treatment process. The radiology support system in the diagnostic process allows faster and more accurate radiographic contouring. The aim of the paper is to present a new method for ultrasound image segmentation of breast lesions. The segmentation technique is based on active contour models whereas anisotropic diffusion is used for preprocessing. The Dice Index calculated in most of analyzed cases was greater than 80%. Delineation of the tumor can also be used to calculate the size and volume automatically, and shortened the time of the diagnosis.

Parametric Curves in Liver Deformation for Laparoscopic Purposes

An increasing number of conducted endoscopic procedures results in inventing new computer systems, that would be a helpful tool in this kind of medical examinations. In this paper the need of evaluating algorithms describing the deformation of internal organs for laparoscopic surgery purposes is presented. A possible solution to the problem of visualising such deformations has been suggested. Furthermore, the way of collecting data by studying the liver reaction to an external force was described. A model of the liver deformations based on Bezier curves has been developed and compared with the shape of the real liver deformation.