Computed tomography (CT) and magnetic resonance (MR) imaging have been widely used for visualizing the inside of the human body. However, in many cases, pathological diagnosis is conducted through a biopsy or resection of an organ to evaluate the condition of tissues as definitive diagnosis. To provide more advanced information onto CT or MR image, it is necessary to reveal the relationship between tissue information and image signals. We propose a registration scheme for a set of PT images of divided specimens and a 3D-MR image by reference to an optical macro image (OM image) captured by an optical camera. We conducted a fundamental study using a resected human brain after the death of a brain cancer patient. We constructed two kinds of registration processes using the OM image as the base for both registrations to make conversion parameters between the PT and MR images. The aligned PT images had shapes similar to the OM image. On the other hand, the extracted cross-sectional MR image was similar to the OM image. From these resultant conversion parameters, the corresponding region on the PT image could be searched and displayed when an arbitrary pixel on the MR image was selected. The relationship between the PT and MR images of the whole brain can be analyzed using the proposed method. We confirmed that same regions between the PT and MR images could be searched and displayed using resultant information obtained by the proposed method. In terms of the accuracy of proposed method, the TREs were 0.56 ± 0.39 mm and 0.87 ± 0.42 mm. We can analyze the relationship between tissue information and MR signals using the proposed method.

Laparoscopic surgery allows reduction in surgical incision size and leads to faster recovery compared with open surgery. When bleeding takes place, hemostasis treatment is planned according to the state and location of the bleeding. However, it is difficult to find the bleeding source due to low visibility caused by the narrow field of view of the laparoscope. In this paper, we propose the concept of a hemostasis support system that automatically identifies blood regions and indicates them to the surgeon. We mainly describe a blood region identification method that is one of technical challenges to realize the support system. The proposed method is based on a machine learning technique called the support vector machine, working in real time. Within this method, all the pixels in the image are classified as either blood or non-blood pixels based on color features (e.g., a combination of RGB and HSV values). The suitable combination of feature values used for the classification is determined by a simple feature selection method. Three feature values were determined to identify the blood region. We then validated the proposed method with ten sequences of laparoscopic images by cross-validation. The average accuracy exceeded 95% with a processing time of about 12.6 ms/frame. The proposed method was able to accurately identify blood regions and was suitable for real-time applications.

In diagnosis and treatment of knee joint diseases, it is effective to study the three-dimensional (3D) motion of the patient's knee joint involving the femur, tibia, and patella. A 2D/3D registration method with use of fluoroscopy and CT images is promising for this purpose. However, there is no report showing whether the dynamic 3D motion of the patella can be obtained. In this study, we tried to examine dynamic 3D motion of the knee joint which included the patella. First, in order to investigate the accuracy of the position estimation, we conducted an experiment on a pig knee joint which had several fiducial markers placed on it, and we found that errors in the estimation of rotation and translation were less than 1 mm and 1 deg. We then carried out an image-acquisition experiment with healthy knee joints of three volunteers and confirmed that 3D motions of the femur, tibia, and patella were successfully obtained for all cases.

BackgroundThe aims of this study were to reveal the characteristics of the meniscal shape at each knee osteoarthritis (OA) severity level and to predict trends or patterns of the meniscal shape change as associated with knee OA progression.MethodsFifty-one patients diagnosed with knee OA based on X-ray and magnetic resonance (MR) images were evaluated. They were divided into three groups based on the Kellgren–Lawrence (KL) grade: normal group (KL grade of 0 or 1), mild group (KL grade of 2 or 3), and severe group (KL grade of 4). We measured the patients’ meniscal size and meniscal extrusion using MR images. In addition, semiquantitative measurement was performed using MR images to determine the arthritic status of the corresponding compartment using a whole-organ magnetic resonance imaging score (WORMS).ResultsThe longitudinal diameter and posterior wedge angle of the medial meniscus were significantly larger, and the posterior wedge width of the medial meniscus was significantly smaller in the severe group than in the normal group. The WORMS scores for cartilage and osteophytes in the medial region were significantly different among the groups. The WORMS score of each region was strongly correlated with the longitudinal diameter. The WORMS scores of the lateral region were lower than those of the medial region.ConclusionOur observation of the shape change of the medial meniscus in the posterior region was roughly consistent with that in many previous studies of meniscal degeneration. On the other hand, we saw that the most relevant relation between the progression of the knee OA and the deformation of the meniscus was in the longitudinal direction.

When surgeons evaluate the condition of organs and make diagnoses, color difference is important information despite its subtleness. Yielding clearer views of blood circulation holds the key to successful surgeries such as transplants and anastomosis. Optimization of surgical illuminant is one approach to clearer views. Our previous study focused on computer simulation to enhance color difference. In the present study, we improved the simulation method by applying a color appearance model CIECAM02 and we realized an optimized illuminant based on the simulation. In an evaluation experiment comparing the optimal illuminant with the conventional illuminant, fourteen LEDs fixed to the light unit were spectrally adjusted to demonstrate the two illuminants. Using a rat cecum, we observed the color differences under two conditions: normal blood flow and restricted blood flow. The color difference under the optimal illuminant was greater than under the conventional illuminant and the effectiveness of the optimal illuminant was confirmed.

We propose a red, green, blue (RGB)-based oximetry to assess the ocular fundus and determine its oxygen saturation (SO 2 ) and hemoglobin concentration. The oxygenated hemoglobin concentration, deoxygenated hemoglobin concentration, and SO 2 were estimated employing a method that combines Monte Carlo simulation of light transport in the fundus tissue with a multiple regression analysis. In this study, a single-layer model of the ocular fundus was employed for the Monte Carlo simulation. We constructed an experimental apparatus for measuring the fundus of a rat's eye using an RGB detector and investigated the physiological response that occurs upon a change in the fraction of inspired oxygen (FiO 2 ). The resultant images of oxygenated hemoglobin concentration, deoxygenated hemoglobin concentration, total hemoglobin concentration, and SO 2 indicated that the response was caused by the defective oxygenation of the blood. The results of the present study indicate the possibility of oximetry based on the RGB images of a fundus.INDEX TERMS Digital cameras, biomedical optical imaging, image color analysis.

Monitoring oxygen saturation (SO 2) in microcirculation is effective for understanding disease dynamics. We have developed an SO 2 estimation method, sidestream dark-field (SDF) oximetry, based on SDF imaging. SDF imaging is a noninvasive and clinically applicable technique to observe microcirculation. We report the first in vivo experiment observing the changes in SO 2 of microcirculation using SDF oximetry. First, heat from the light-emitting diodes used for the SDF imaging might affect hemodynamics in microcirculation, hence, we performed an experiment to evaluate the influence of that on the SDF oximetry. The result suggested that SDF oximetry had enough stability for long-term experiments. Then, to evaluate the sensitivity of SDF oximetry to alterations in the hemodynamics of the microcirculation, we observed the time-lapsed SO 2 changes in the dermis microcirculation of rats under hypoxic stimulation. We confirmed that the SO 2 estimated by SDF oximetry was in accordance with changes in the fraction of inspired oxygen (FiO 2). Thus, SDF oximetry is considered to be able to observe SO 2 changes that occur in accordance with alteration of the microcirculation.

BackgroundIn the progression of osteoarthritis (OA) of the knee, a correlation between meniscal posterior segment injuries and medial meniscal extrusion has been reported, but there have been few reports on the relationship with the meniscal shape. The purpose of this study was to clarify the features of the meniscal shape involved in the progression of knee OA.MethodsData were obtained from the Osteoarthritis Initiative (OAI) database. We defined two sets of subjects. One set included 455 knees of subjects whose OA grade on the Kellgren Lawrence (KL) scale progressed in 24 months from baseline and the other set consisted of 455 knees with no progression. The OA progressed subjects were divided to three groups: the “OA change group”, KL0 and KL1 knees that progressed to KL2 and KL3; the “mild change group”, KL2 knees that progressed to KL3; and the “severe change group”, KL2 and KL3 knees that progressed to KL4. The no progression set was divided into three groups whose OA grade remained unchanged. We used magnetic resonance imaging data and manually measured seven items (longitudinal diameter [LD], anterior wedge thickness, anterior wedge width, posterior wedge width, posterior wedge thickness, anterior wedge angle, posterior wedge angle) from the sagittal slice and the extrusion from the coronal slice. These measurements were compared between knees with and without OA progression.ResultsIn the “OA change group” and “mild change group”, the anterior and posterior wedge widths and the extrusion were significantly larger, but the anterior and the posterior wedge angles were significantly smaller. In the “severe change group,” the LD and the extrusion were significantly larger. In each group, there was no uniform tendency for the correlation coefficient of the parameters evaluated.ConclusionsOur findings suggested (1) a larger meniscal LD at the baseline predicted progression of knee OA after 24 months and (2) a larger meniscal width and smaller meniscal angle predicted progression of knee OA after 24 months.