Deep CNN for IIF Images Classification in Autoimmune Diagnostics

The diagnosis and monitoring of autoimmune diseases are very important problem in medicine. The most used test for this purpose is the antinuclear antibody (ANA) test. An indirect immunofluorescence (IIF) test performed by Human Epithelial type 2 (HEp-2) cells as substrate antigen is the most common methods to determine ANA. In this paper we present an automatic HEp-2 specimen system based on a convolutional neural network method able to classify IIF images. The system consists of a module for features extraction based on a pre-trained AlexNet network and a classification phase for the cell-pattern association using six support vector machines and a k-nearest neighbors classifier. The classification at the image-level was obtained by analyzing the pattern prevalence at cell-level. The layers of the pre-trained network and various system parameters were evaluated in order to optimize the process. This system has been developed and tested on the HEp-2 images indirect immunofluorescence images analysis (I3A) public database. To test the generalisation performance of the method, the leave-one-specimen-out procedure was used in this work. The performance analysis showed an accuracy of 96.4% and a mean class accuracy equal to 93.8%. The results have been evaluated comparing them with some of the most representative works using the same database

HEp-2 Cell Classification with heterogeneous classes-processes based on K-Nearest Neighbours

We present a scheme for the feature extraction and classification of the fluorescence staining patterns of HEp-2 cells in IIF images. We propose a set of complementary processes specific to each class of patterns to search. Our set of processes consists of preprocessing,features extraction and classification. The choice of methods, features and parameters was performed automatically, using the Mean Class Accuracy (MCA) as a figure of merit. We extract a large number (108) of features able to fully characterize the staining pattern of HEp-2 cells. We propose a classification approach based on two steps: the first step follows the one-against-all(OAA) scheme, while the second step follows the one-against-one (OAO) scheme. To do this, we needed to implement 21 KNN classifiers: 6 OAA and 15 OAO. Leave-one-out image cross validation method was used for the evaluation of the results

Pulsed Electric Fields (PEF) applications in the inactivation of parasites in food

Background Parasites are concerning food-borne pathogens. Some of them are currently not being routinely controlled in food, probably because their burden on public health is underestimated and the relative importance of different transmission routes is not completely known. Parasitic incidences could be avoided if preventive technologies were applied during food processing. Effective inactivation treatments are currently based on heat or freezing, but their side effects collide head-on with current consumer trends and new culinary habits. Scope and approach This review describes the potential application of Pulsed Electric Field (PEF) technology in the control of food-borne parasites, with the aim of reducing the viability and infectivity of parasite transmission stages without affecting food quality. Results of published studies performed on different media are critically analyzed and factors affecting the outcomes are examined. Key findings and conclusions Recent studies on the topic demonstrate the feasibility of PEF as an alternative to traditional freezing processes for the inactivation of Anisakis in fish. The development of new PEF equipment is advancing at a rapid pace, allowing for food treatment at a scale that would have been unimaginable some years ago. A review of more basic-science studies carried out on buffer media would contribute to progress in addressing the underlying drawbacks that remain to be solved. Thoroughly different fields (parasitology, physics, food engineering, water sanitation, etc.) should converge to achieve the industrial implementation of PEF for the inactivation of food-borne parasites

Cancer patients requiring interruption of long-term warfarin because of surgery or chemotherapy induced thrombocytopenia: the use of fixed sub-therapeutic doses of low-molecular weight heparin.

No data are available regarding the management of cancer patients requiring interruption of long-term vitamin-K antagonist (VKA) therapy. For this purpose, we tested the efficacy and safety of fixed doses of low-molecular weight heparin (LMWH) in substitution of VKA because of invasive procedures or chemotherapy-induced thrombocytopenia. In cancer patients on VKA, therapy was discontinued 5 ± 1 days before surgery or chemotherapy. Heparin was given at prophylactic dosage in patients at low risk and at fixed subtherapeutic doses (3,800 or 4,000 UI anti-FXa, b.i.d.) in those at high-risk for thrombosis. LMWH was reinitiated 12 hr after surgery and VKA the day after. In patients receiving chemotherapy, LMWH was reinitiated 12/24 hr after obtaining a stable platelet count ≥ 30,000 mmc(3) and VKA after a stable platelet count ≥ 50,000 mmc(3) . Thromboembolism and major bleeding events were recorded from the time of VKA suspension to 30 ± 2 days postprocedure or until the next chemotherapy. Overall, 156 patients (56.4% at low risk and 43.5% at high risk for thrombosis) were enrolled; 34.6% underwent major surgery, 40.4% nonmajor surgery, and 25% chemotherapy. Thrombotic events occurred in five patients [3.2%, 95% confidence interval (CI): 1.41-7.27], four belonging to the high-risk and one to the low-risk group. Major bleeding occurred in five patients (3.2%, 95 CI: 1.41-7.27), all belonging to the high-risk group (three during major surgery and two during chemotherapy). In conclusion, LMWH given at fixed subtherapeutic is a feasible and relatively safe approach for bridging therapy in cancer patients on long-term VK

Massive pulmonary embolism as a rare complication of a stab in the inguinal region in a HIV-positive patient: a case report

Venous thromboembolism (VTE) is a severe preventable disease; HIV-infection represents a prothrombotic condition, because of specific factors due to the virus itself, the host response and the antiretroviral therapy. Our aim is to raise awareness of thromboembolic risk when dealing with HIV-positive patients presenting to the Emergency Department for treatment of injuries, even though small

A REST-based framework to support non-invasive and early coeliac disease diagnosis

The health sector has traditionally been one of the early adopters of databases, from the most simple Electronic Health Record (formerly Computer-Based Patient Record) systems in use in general practice, hospitals and intensive care units to big data, multidata based systems used to support diagnosis and care decisions. In this paper we present a framework to support non-invasive and early diagnosis of coeliac disease. The proposed framework makes use of well-known technologies and techniques, both hardware and software, put together in a novel way. The main goals of our framework are: (1) providing users with a reliable and fast repository of a large amount of data; (2) to make such repository accessible by means of a suitable API in multiple modes, such as intuitive web-based or mobile visual interfaces; (3) to allow for data processing and analysis, as a basis for decision support systems

Automated Stabilization, Enhancement and Capillaries Segmentation in Videocapillaroscopy

Oral capillaroscopy is a critical and non-invasive technique used to evaluate microcirculation. Its ability to observe small vessels in vivo has generated significant interest in the field. Capillaroscopy serves as an essential tool for diagnosing and prognosing various pathologies, with anatomic–pathological lesions playing a crucial role in their progression. Despite its importance, the utilization of videocapillaroscopy in the oral cavity encounters limitations due to the acquisition setup, encompassing spatial and temporal resolutions of the video camera, objective magnification, and physical probe dimensions. Moreover, the operator’s influence during the acquisition process, particularly how the probe is maneuvered, further affects its effectiveness. This study aims to address these challenges and improve data reliability by developing a computerized support system for microcirculation analysis. The designed system performs stabilization, enhancement and automatic segmentation of capillaries in oral mucosal video sequences. The stabilization phase was performed by means of a method based on the coupling of seed points in a classification process. The enhancement process implemented was based on the temporal analysis of the capillaroscopic frames. Finally, an automatic segmentation phase of the capillaries was implemented with the additional objective of quantitatively assessing the signal improvement achieved through the developed techniques. Specifically, transfer learning of the renowned U-net deep network was implemented for this purpose. The proposed method underwent testing on a database with ground truth obtained from expert manual segmentation. The obtained results demonstrate an achieved Jaccard index of 90.1% and an accuracy of 96.2%, highlighting the effectiveness of the developed techniques in oral capillaroscopy. In conclusion, these promising outcomes encourage the utilization of this method to assist in the diagnosis and monitoring of conditions that impact microcirculation, such as rheumatologic or cardiovascular disorders