ARTICLE | doi:10.20944/preprints202104.0573.v1
Subject: Engineering, Automotive Engineering Keywords: fluorescence microscopy; fluorescence emission, malignant tumor, diagnosis, animal experiment
Online: 21 April 2021 (11:47:14 CEST)
A surgical microscope is large in size, which makes it impossible to be portable. The distance between the surgical microscope and the observation tissue is 15–30 cm, and the adjustment range of the right and left of the camera is a maximum of 30°. Therefore, the surgical microscope is generated attenuation (above 58%) of irradiation optical source owing to the long working distance. Moreover, the observation of tissue is affected because of dazzling by ambient light as the optical source power is strong (55 to 160 mW/cm2). Further, observation blind spot phenomena will occur due to the limitations in adjusting the right and left of the camera. Therefore, it is difficult to clearly observe the tumor. In this study, a compact pen-type probe with a portable surgical microscope is presented. The proposed surgical microscope comprises a small and portable pen-type probe that can adjust the working distance between the probe and the observed tissue. In addition, it allows the adjustment of the viewing angle and fluorescence brightness. The proposed probe has no blind spots or optical density loss.
ARTICLE | doi:10.20944/preprints202104.0557.v1
Subject: Engineering, Automotive Engineering Keywords: fluorescence microscopy; fluorescence emission; malignant tumor; diagnosis; animal experiment
Online: 21 April 2021 (08:30:11 CEST)
A surgical microscope is large in size, making portability impossible. The distance between the surgical microscope and the observation tissue is 15 to 30 cm, while the maximum adjustment range of the camera to the right and left is 30°. Therefore, surgical microscopes cause attenuation (above 58%) of the irradiation optical source owing to the long working distance. Moreover, the observation of tissue was dazzled with ambient light because the optical power source was strong (50 to 160 mW/cm2). Owing to the limited ability to adjust the camera to the right and left, a blind spot occurs with a surgical microscope. Therefore, it is difficult to clearly observe a tumor. In this study, a compact pen-type probe with a portable surgical microscope is proposed. The pen-type probe is small with a portable shape, and is capable of adjusting the working distance between itself and the observed tissue. It is also possible to adjust the viewing angle and fluorescence brightness. The proposed pen-type probe has no blind spots or optical density loss.
ARTICLE | doi:10.20944/preprints202203.0140.v1
Subject: Mathematics & Computer Science, Artificial Intelligence & Robotics Keywords: Left ventricular ejection fraction; Left ventricle segmentation; Convolutional long short-term memory; Echocardiography
Online: 10 March 2022 (04:19:30 CET)
Cardiovascular disease is the leading cause of death worldwide. A key factor in assessing the risk of cardiovascular disease is left ventricular functional evaluation. Left ventricular (LV) systolic function is evaluated by measuring the left ventricular ejection fraction (LVEF) using echocardiography data. Therefore, quick and accurate left ventricle segmentation is important for estimating the LVEF. However, it is difficult to accurately segment the left ventricle due to changes in the shape and area of the left ventricle during cardiac cycles. In this study, we proposed a framework that considers changes in the shape and area of the left ventricle during the cardiac cycle by applying the convolutional long short-term memory (CLSTM) approach. In addition, we evaluated the left ventricular segmentation and multidimensional quantification of the proposed system in comparison to manual and automated segmentation methods. In addition, to assess the validity of CLSTM, the values of multi-dimensional quantification metrics were compared and analyzed using graphs and Bland–Altman plots on a frame-by-frame basis. We demonstrated that the CLSTM method effectively segments the left ventricle by considering the LV activity. In conclusion, we demonstrated that LV segmentation based on our framework may be utilized to accurately estimate LVEF values.