Microaneurysm detection using deep learning and interleaved freezing

Diabetes affects one in eleven adults. Diabetic retinopathy is a microvascular complication of diabetes and the leading cause of blindness in the working-age population. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper proposes an automatic method for detecting microaneurysms in fundus photographies. A novel patch-based fully convolutional neural network for detection of microaneurysms is proposed. Compared to other methods that require five processing stages, it requires only two. Furthermore, a novel network fine-tuning scheme called Interleaved Freezing is presented. This procedure significantly reduces the amount of time needed to re-train a network and produces competitive results. The proposed method was evaluated using publicly available and widely used datasets: E-Ophtha and ROC. It outperforms the state-of-the-art methods in terms of free-response receiver operatic characteristic (FROC) metric. Simplicity, performance, efficiency and robustness of the proposed method demonstrates its suitability for diabetic retinopathy screening applications

Exudate segmentation using fully convolutional neural networks and inception modules

Diabetic retinopathy is an eye disease associated with diabetes mellitus and also it is the leading cause of preventable blindness in working-age population. Early detection and treatment of DR is essential to prevent vision loss. Exudates are one of the earliest signs of diabetic retinopathy. This paper proposes an automatic method for the detection and segmentation of exudates in fundus photographies. A novel fully convolutional neural network architecture with Inception modules is proposed. Compared to other methods it does not require the removal of other anatomical structures. Furthermore, a transfer learning approach is applied between small datasets of different modalities from the same domain. To the best of authors’ knowledge, it is the first time that such approach has been used in the exudate segmentation domain. The proposed method was evaluated using publicly available E-Ophtha datasets. It achieved better results than the state-of-the-art methods in terms of sensitivity and specificity metrics. The proposed algorithm accomplished better results using a diseased/not diseased evaluation scenario which indicates its applicability for screening purposes. Simplicity, performance, efficiency and robustness of the proposed method demonstrate its suitability for diabetic retinopathy screening applications

Microaneurysm detection using fully convolutional neural networks

Backround and Objectives: Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper presents an automatic method for detecting microaneurysms in fundus photographies. Methods: A novel patch-based fully convolutional neural network with batch normalization layers and Dice loss function is proposed. Compared to other methods that require up to five processing stages, it requires only three. Furthermore, to the best of the authors’ knowledge, this is the first paper that shows how to successfully transfer knowledge between datasets in the microaneurysm detection domain. Results: The proposed method was evaluated using three publicly available and widely used datasets: E-Ophtha, DIARETDB1, and ROC. It achieved better results than state-of-the-art methods using the FROC metric. The proposed algorithm accomplished highest sensitivities for low false positive rates, which is particularly important for screening purposes. Conclusions: Performance, simplicity, and robustness of the proposed method demonstrates its suitability for diabetic retinopathy screening applications

Hemodynamics in the retinal vasculature during the progression of diabetic retinopathy

Purpose: Several studies have established, using various measurement modalities, that progression from diabetes to diabetic retinopathy is associated with changes in haemodynamics or measurable vascular geometry. In this study we take vessel measurements from standard fundus images, and estimate haemodynamic parameters (which are not directly observable) using a simple haemodynamic model. We show that there are statistically significant changes in some estimated haemodynamic parameters associated with the development of DR. Methods: A longitudinal study of twenty-four subjects was conducted. For each subject four fundus images were used, taken annually during the three years before the appearance of DR and in the first year of DR. A venous and arterial vascular bifurcation, each of which consisted of a parent vessel and two child branches was extracted, and at the branching nodes a zero dimensional model estimated the fluid dynamic conditions in terms of volumetric blood flow, blood flow velocity, nodal pressure, wall shear stress and Reynolds number. These features were statistically analyzed using linear mixed models. Results: A number of parameters, primarily venous, showed significant change with the development of DR, including early change two years before the onset of DR. A large proportion of overall variance is accounted for by individual patient differences, making progressive study essential. Conclusion: This is the first paper to demonstrate that haemodynamic feature estimates extracted from standard fundus images are sensitive to progression from diabetes to DR. In our future work, we aim to test whether the variations in haemodynamic conditions are predictive of progression prior to the appearance of retinal lesions

A fluid-dynamic based approach to reconnect the retinal vessels in fundus photography

This paper introduces the use of fluid-dynamic modeling to determine the connectivity of overlapping venous and arterial vessels in fundus images. Analysis of the retinal vascular network may provide information related to systemic and local disorders. However, the automated identification of the vascular trees in retinal images is a challenging task due to the low signal-to-noise ratio, nonuniform illumination and the fact that fundus photography is a projection on to the imaging plane of three-dimensional retinal tissue. A zero-dimensional model was created to estimate the hemodynamic status of candidate tree configurations. Simulated annealing was used to search for an optimal configuration. Experimental results indicate that simulated annealing was very efficient on test cases that range from small to medium size networks, while ineffective on large networks. Although for large networks the nonconvexity of the cost function and the large solution space made searching for the optimal solution difficult, the accuracy (average success rate = 98.35%), and simplicity of our novel approach demonstrate its potential effectiveness in segmenting retinal vascular trees

Mobile Real-Time Grasshopper Detection and Data Aggregation Framework

nsects of the family Orthoptera: Acrididae including grasshoppers and locust devastate crops and eco-systems around the globe. The effective control of these insects requires large numbers of trained extension agents who try to spot concentrations of the insects on the ground so that they can be destroyed before they take flight. This is a challenging and difficult task. No automatic detection system is yet available to increase scouting productivity, data scale and fidelity. Here we demonstrate MAESTRO, a novel grasshopper detection framework that deploys deep learning within RBG images to detect insects. MAeStRo uses a state-of-the-art two-stage training deep learning approach. the framework can be deployed not only on desktop computers but also on edge devices without internet connection such as smartphones. MAeStRo can gather data using cloud storage for further research and in-depth analysis. In addition, we provide a challenging new open dataset (GHCID) of highly variable grasshopper populations imaged in inner Mongolia. the detection performance of the stationary method and the mobile App are 78 and 49 percent respectively; the stationary method requires around 1000 ms to analyze a single image, whereas the mobile app uses only around 400 ms per image. The algorithms are purely data-driven and can be used for other detection tasks in agriculture (e.g. plant disease detection) and beyond. This system can play a crucial role in the collection and analysis of data to enable more effective control of this critical global pest

Removal of foreign bodies from the airways and esophagus development of the method and equipment over the centuries

The problem of aspiration of foreign bodies was already known in antiquity. The first described death of man was the case of the Greek poet Anakreon, who in 475 BC choked himself with a grape. Initially, the treatment was limited to the pneumonia caused by the presence of a foreign body, then treatment of surgical procedures was attempted. The first documented case of tracheotomy (known as bronchotomy) for removing a foreign body was described in 1717 by Verdue. Unfortunately there was a significant disadvantage of the devices used to remove foreign bodies from the airways and esophagus - lack of a proper light source. At the beginning doctors were using candles, but their light was insufficient to observe anatomical structures. Philipp Bozzini developed the first light source which allowed to view the upper part of the esophagus - He called it a "lichtleiter". However a milestone in the endoscopy was made by the French urologist Antonin Desormeaux. He presented an improved device, which he called the "endoscope". For this reason, he was hailed as "father of endoscopy". Nevertheless scientific and technical progress is still continuing. Doctors have at their disposal more and more modern equipment for the diagnosis and removal of foreign bodies from the airways and esophagus. But even the most perfect endoscope will not replace the doctor's skills combined with assurance of maximum safety during and immediately after the procedure

Evaluation and management of pain in geriatric patients who were diagnosed in Emergency Department

Introduction and purpose of the work. Pain is one of the most common causes of medical rescue teams’ callings. Most of the cases are solved at patients’ homes. Some problems presented by geriatric patients are too difficult to be evaluated at home and need to be admitted to hospitals’ emergency departments(ED) for further diagnosis. Geriatric patients are often burdened with multiorgan dysfunctions which can cause pain. This problem in senior population is often overlooked or underestimated Material and method. Survey was conducted among 100 patients after 65 years of age who were admitted to ED because of pain. Location, the intensity of pain before and after application of analgesia, vital signs( heart rate, blood pressure, the number of breaths, temperature), previously administered pain killers and sociodemographic factors were evaluated and noted Results. Women predominated in the study group as well as the patients with posttraumatic pain (mostly fall from the same height). Forty five percent of patients took a painkiller at home. Preliminary average rating of pain numeric scale (NRS) was 7.49 points. Respondents who received painkillers before coming to the ED, felt more severe pain than those who did not take medications (NRS 7.93 vs. 7.41). Thirty minutes after application of analgesic pain intensity averaged 3.74 points. Conclusions. Pain is a common cause among elderly patients who report to ED, despite previously adopted analgesics. It remains underestimated in prehospital care and needs special attention in emergency departments

Mesothelioma - a growing medical problem with heterogeneous course

Mesothelioma is one of the most malignant neoplasms affecting the thin lining of the body's internal organs, known as the mesothelium. The incidence of mesothelioma in recent years has increased. It is assumed that the reason for this situation is the exposure in the past to natural mineral fibers (nickel, beryllium, silica dust), ionizing radiation, some organic compounds and SV40 virus but mostly to asbestos. The time from contact to the first symptoms is about 20-40 years. Probably the peak of morbidity is yet to come. Due to non-specific symptoms such as chest pain, shortness of breath, fluid in the pleural cavity, early detection is very difficult. Additionally, we can deal with mesothelioma which starting point is outside the pleural cavity. In such cases, diagnostics is even more difficult, because the only remaining symptom is pain. Therefore, it is important to pay attention to this growing problem

Stymulacja dwupunktowa prawej komory jako alternatywna metoda leczenia pacjentów z asynchronią lewokomorową po nieudanej implantacji elektrody lewokomorowej układu resynchronizującego

Wstęp: Stymulacja resynchronizująca serca (CRT) jest uznaną metodą leczenia wyselekcjonowanych pacjentów z zaawansowaną niewydolnością serca, lecz u 5-15% chorych warunki anatomiczne uniemożliwiają implantację elektrody lewokomorowej. Epikardialna implantacja wiąże się z ryzykiem powikłań okołooperacyjnych, zwiększa koszty zabiegu i jest dostępna tylko w ośrodkach, w których istnieje możliwość przeprowadzenia procedur kardiochirurgicznych. Istnieją dane świadczące, że stymulacja 2-punktowa w prawej komorze poprawia parametry hemodynamiczne w porównaniu z klasyczną stymulacją wierzchołkową, zwłaszcza u pacjentów z niewydolnością serca. Celem pracy była kliniczna oraz echokardiograficzna ocena osób, u których z powodów technicznych (anatomicznych bądź elektrofizjologicznych) nie zdołano implantować w pożądanym miejscu elektrody lewokomorowej przez zatokę wieńcową i u których implantowano układ stymulujący z 2-punktową stymulacją prawej komory. Materiał i metody: Badania przeprowadzono u 8 chorych w wieku śr. 65 ± 9 lat, u których ze względu na trudności techniczne implantowano układ z 2-punktową stymulacją prawej komory. Wszyscy pacjenci mieli wskazania do implantacji CRT. U 3 chorych rozpoznano kardiomiopatię pozawałową, u pozostałych 5 - idiopatyczną kardiomiopatię zastoinową. U wszystkich pacjentów występowała znacząca (IV klasa czynnościowa wg NYHA), skurczowa (śr. LVEF = 22%) niewydolność serca i znaczące zaburzenia przewodzenia międzykomorowego (śr. czas trwania zespołów QRS = 180 ms). Pacjenci otrzymali przedsionkowo-komorowy układ stymulujący z dodatkową elektrodą w drodze odpływu prawej komory oraz stymulator Stratos LV. Wyniki: U każdego z pacjentów po włączeniu 2-punktowej stymulacji prawej komory pokonanywany dystans podczas 6-minutowego marszu wydłużył się w porównaniu z testem wykonanym przy natywnej aktywacji komór, a średnia różnica pokonanego dystansu była istotna statystycznie. Stymulacja 2-punktowa w prawej komorze nie spowodowała znamiennej różnicy w średniej szerokości zespołów QRS w elektrokardiogramie rejestrowanym przed zabiegiem (aktywacja natywna) i po zabiegu (rytm stymulatorowy). W badaniu echokardigraficznym wykazano, że po zastosowaniu 2-punktowej stymulacji prawej komory wskaźnik asynchronii międzykomorowej uległ istotnemu zmniejszeniu w porównaniu z badaniem podstawowym. Znamiennie zmniejszył się wymiar skurczowy lewej komory, któremu towarzyszył istotny wzrost frakcji wyrzutowej, pojemności minutowej i wskaźnika sercowego. Wniosek: Stymulacja 2-punktowa prawej komory może być interesującą opcją terapeutyczną dla pacjentów ze wskazaniami do resynchronizacji serca i nieudaną próbą implantacji elektrody lewokomorowej