An Interactive Approach to Region of Interest Selection in Cytologic Analysis of Uveal Melanoma Based on Unsupervised Clustering

Author(s):  
Haomin Chen ◽  
T. Y. Alvin Liu ◽  
Zelia Correa ◽  
Mathias Unberath
Aerospace ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 42 ◽  
Author(s):  
Yousef Azabi ◽  
Al Savvaris ◽  
Timoleon Kipouros

In this work, an interactive optimisation framework—a combination of a low fidelity flow solver, Athena Vortex Lattice (AVL), and an interactive Multi-Objective Particle Swarm Optimisation (MOPSO)—is proposed for aerodynamic shape design optimisation of any aerial vehicle platform. This paper demonstrates the benefits of interactive optimisation—reduction of computational time with high optimality levels. Progress towards the most preferred solutions is made by having the Decision Maker (DM) periodically provide preference information once the MOPSO iterations are underway. By involving the DM within the optimisation process, the search is directed to the region of interest, which accelerates the process. The flexibility and efficiency of undertaking optimisation interactively have been demonstrated by comparing the interactive results with the non-interactive results of an optimum design case obtained using Multi-Objective Tabu Search (MOTS) for the Aegis UAV. The obtained results show the superiority of using an interactive approach for the aerodynamic shape design, compared to posteriori approaches. By carrying out the optimisation using interactive MOPSO it was shown to be possible to obtain similar results to non-interactive MOTS with only half the evaluations. Moreover, much of the usual complexity of post-data-analysis with posteriori approaches is avoided, since the DM is involved in the search process.


2019 ◽  
Vol 16 (04) ◽  
pp. 1950015
Author(s):  
Xiaoyan Wang ◽  
Xingyu Zhong ◽  
Ming Xia ◽  
Weiwei Jiang ◽  
Xiaojie Huang ◽  
...  

Localization of vessel Region of Interest (ROI) from medical images provides an interactive approach that can assist doctors in evaluating carotid artery diseases. Accurate vessel detection is a prerequisite for the following procedures, like wall segmentation, plaque identification and 3D reconstruction. Deep learning models such as CNN have been widely used in medical image processing, and achieve state-of-the-art performance. Faster R-CNN is one of the most representative and successful methods for object detection. Using outputs of feature maps in different layers has been proved to be a useful way to improve the detection performance, however, the common method is to ensemble outputs of different layers directly, and the special characteristic and different importance of each layer haven’t been considered. In this work, we introduce a new network named Attention Layer R-CNN(AL R-CNN) and use it for automatic carotid artery detection, in which we integrate a new module named Attention Layer Part (ALP) into a basic Faster R-CNN system for better assembling feature maps of different layers. Experimental results on carotid dataset show that our method surpasses other state-of-the-art object detection systems.


Author(s):  
R.J. Mount ◽  
R.V. Harrison

The sensory end organ of the ear, the organ of Corti, rests on a thin basilar membrane which lies between the bone of the central modiolus and the bony wall of the cochlea. In vivo, the organ of Corti is protected by the bony wall which totally surrounds it. In order to examine the sensory epithelium by scanning electron microscopy it is necessary to dissect away the protective bone and expose the region of interest (Fig. 1). This leaves the fragile organ of Corti susceptible to physical damage during subsequent handling. In our laboratory cochlear specimens, after dissection, are routinely prepared by the O-T- O-T-O technique, critical point dried and then lightly sputter coated with gold. This processing involves considerable specimen handling including several hours on a rotator during which the organ of Corti is at risk of being physically damaged. The following procedure uses low cost, readily available materials to hold the specimen during processing ,preventing physical damage while allowing an unhindered exchange of fluids.Following fixation, the cochlea is dehydrated to 70% ethanol then dissected under ethanol to prevent air drying. The holder is prepared by punching a hole in the flexible snap cap of a Wheaton vial with a paper hole punch. A small amount of two component epoxy putty is well mixed then pushed through the hole in the cap. The putty on the inner cap is formed into a “cup” to hold the specimen (Fig. 2), the putty on the outside is smoothed into a “button” to give good attachment even when the cap is flexed during handling (Fig. 3). The cap is submerged in the 70% ethanol, the bone at the base of the cochlea is seated into the cup and the sides of the cup squeezed with forceps to grip it (Fig.4). Several types of epoxy putty have been tried, most are either soluble in ethanol to some degree or do not set in ethanol. The only putty we find successful is “DUROtm MASTERMENDtm Epoxy Extra Strength Ribbon” (Loctite Corp., Cleveland, Ohio), this is a blue and yellow ribbon which is kneaded to form a green putty, it is available at many hardware stores.


2015 ◽  
Vol 21 ◽  
pp. 194-195
Author(s):  
Rokshana Thanadar ◽  
Uzma Siddiqui ◽  
Marie Lithgow ◽  
Runhua Hou

2004 ◽  
Vol 43 (06) ◽  
pp. 185-189 ◽  
Author(s):  
J. T. Kuikka

Summary Aim: Serotonin transporter (SERT) imaging can be used to study the role of regional abnormalities of neurotransmitter release in various mental disorders and to study the mechanism of action of therapeutic drugs or drugs’ abuse. We examine the quantitative accuracy and reproducibility that can be achieved with high-resolution SPECT of serotonergic neurotransmission. Method: Binding potential (BP) of 123I labeled tracer specific for midbrain SERT was assessed in 20 healthy persons. The effects of scatter, attenuation, partial volume, mis-registration and statistical noise were estimated using phantom and human studies. Results: Without any correction, BP was underestimated by 73%. The partial volume error was the major component in this underestimation whereas the most critical error for the reproducibility was misplacement of region of interest (ROI). Conclusion: The proper ROI registration, the use of the multiple head gamma camera with transmission based scatter correction introduce more relevant results. However, due to the small dimensions of the midbrain SERT structures and poor spatial resolution of SPECT, the improvement without the partial volume correction is not great enough to restore the estimate of BP to that of the true one.


2001 ◽  
Vol 40 (04) ◽  
pp. 107-110 ◽  
Author(s):  
B. Roßmüller ◽  
S. Alalp ◽  
S. Fischer ◽  
S. Dresel ◽  
K. Hahn ◽  
...  

SummaryFor assessment of differential renal function (PF) by means of static renal scintigraphy with Tc-99m-dimer-captosuccinic acid (DMSA) the calculation of the geometric mean of counts from the anterior and posterior view is recommended. Aim of this retrospective study was to find out, if the anterior view is necessary to receive an accurate differential renal function by calculating the geometric mean compared to calculating PF using the counts of the posterior view only. Methods: 164 DMSA-scans of 151 children (86 f, 65 m) aged 16 d to 16 a (4.7 ± 3.9 a) were reviewed. The scans were performed using a dual head gamma camera (Picker Prism 2000 XP, low energy ultra high resolution collimator, matrix 256 x 256,300 kcts/view, Zoom: 1.6-2.0). Background corrected values from both kidneys anterior and posterior were obtained. Using region of interest technique PF was calculated using the counts of the dorsal view and compared with the calculated geometric mean [SQR(Ctsdors x Ctsventr]. Results: The differential function of the right kidney was significantly less when compared to the calculation of the geometric mean (p<0.01). The mean difference between the PFgeom and the PFdors was 1.5 ± 1.4%. A difference > 5% (5.0-9.5%) was obtained in only 6/164 scans (3.7%). Three of 6 patients presented with an underestimated PFdors due to dystopic kidneys on the left side in 2 patients and on the right side in one patient. The other 3 patients with a difference >5% did not show any renal abnormality. Conclusion: The calculation of the PF from the posterior view only will give an underestimated value of the right kidney compared to the calculation of the geometric mean. This effect is not relevant for the calculation of the differntial renal function in orthotopic kidneys, so that in these cases the anterior view is not necesssary. However, geometric mean calculation to obtain reliable values for differential renal function should be applied in cases with an obvious anatomical abnormality.


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