New Trends in the Detection of Gynecological Precancerous Lesions and Early-Stage Cancers.

The prevention and early diagnostics of precancerous stages are key aspects of contemporary oncology. In cervical cancer, well-organized screening and vaccination programs, especially in developed countries, are responsible for the dramatic decline of invasive cancer incidence and mortality. Cytological screening has a long and successful history, and the ongoing implementation of HPV triage with increased sensitivity can further decrease mortality.

Electrochemical bioassay coupled to LAMP reaction for determination of high-risk HPV infection in crude lysates.

Electrochemical (EC) detection of DNA biomarkers represents an interesting tool in molecular oncology due to its sensitivity, simplicity, low cost or rapid times of measurement. However, majority of EC assays, same as most optical-based techniques, require preceding DNA extraction step to remove other cellular components, making these assays more laborious and time-consuming. One option to circumvent this is to use LAMP (loop-mediated amplification), an isothermal amplification technique that can amplify DNA directly in crude lysates in a short time at a constant temperature.

Learn to Predict Sets Using Feed-Forward Neural Networks.

This paper addresses the task of set prediction using deep feed-forward neural networks. A set is a collection of elements which is invariant under permutation and the size of a set is not fixed in advance. Many real-world problems, such as image tagging and object detection, have outputs that are naturally expressed as sets of entities.

The role of miR-409-3p in regulation of HPV16/18-E6 mRNA in human cervical high-grade squamous intraepithelial lesions.

Cervical cancer is one of the most common malignancies in women. MicroRNAs (miRNAs) are involved in a variety of fundamental cellular processes, including carcinogenesis. The potential utilization of aberrantly expressed miRNAs as novel biomarkers in cervical cancer diagnostics is growing.

RefineNet: Multi-Path Refinement Networks for Dense Prediction.

Recently, very deep convolutional neural networks (CNNs) have shown outstanding performance in object recognition and have also been the first choice for dense prediction problems such as semantic segmentation and depth estimation. However, repeated subsampling operations like pooling or convolution striding in deep CNNs lead to a significant decrease in the initial image resolution. Here, we present RefineNet, a generic multi-path refinement network that explicitly exploits all the information available along the down-sampling process to enable high-resolution prediction using long-range residual connections.

Genomagnetic LAMP-based electrochemical test for determination of high-risk HPV16 and HPV18 in clinical samples.

Major cause of cervical cancer is a persistent infection with high-risk types of human papillomaviruses (HPV). For that reason, HPV testing is now becoming an important addition to standard cytological screening of cervical malignancies in women (known as Pap test). New methods are sought which could offer rapid and inexpensive detection schemes, such as those based on electrochemical (EC) readout.

Struma ovarii - ultrasound features of a rare tumor mimicking ovarian cancer.

Aims: To describe the ultrasound features of benign struma ovarii that often mimic ovarian cancer in the background of complex clinical and histopathological pictures.

Material And Methods: We retrospectively identified patients with histologically confirmed benign struma ovarii, treated in our institution between 2003-2016 with complete imaging, clinical, nd histopathological data available. Ultrasound findings were drawn from images, and reports using terms and definitions of the International Ovarian Tumor Analysis group and pattern recognition description was applied.

Expression and Functional Characterization of miR-34c in Cervical Cancer.

Background: Cervical cancer is the fourth most common cancer in women and is usually associated with human papillomavirus infection. Viral infections are usually characterized by morphological changes of epithelial cells; however, it is difficult to determine using recently available screening methods whether the changes are caused by productive infection or by malignant disease. Thus, new efforts are required to find novel diagnostic biomarkers of cervical cancer, such as miRNAs, which are small non-coding RNAs involved in the regulation of gene expression.

Electrochemical chip-based genomagnetic assay for detection of high-risk human papillomavirus DNA.

Cervical cancer, being the fourth leading cause of cancer death in women worldwide, predominantly originates from a persistent infection with a high-risk human papillomavirus (HPV). Detection of DNA sequences from these high-risk strains, mostly HPV-16 and HPV-18, represents promising strategy for early screening, which would help to identify women with higher risk of cervical cancer. In developing countries, inadequate screening options lead to disproportionately high mortality rates, making a fast and inexpensive detection schemes highly important.

Multi-Target Tracking by Discrete-Continuous Energy Minimization.

The task of tracking multiple targets is often addressed with the so-called tracking-by-detection paradigm, where the first step is to obtain a set of target hypotheses for each frame independently. Tracking can then be regarded as solving two separate, but tightly coupled problems. The first is to carry out data association, i.

Continuous energy minimization for multitarget tracking.

Many recent advances in multiple target tracking aim at finding a (nearly) optimal set of trajectories within a temporal window. To handle the large space of possible trajectory hypotheses, it is typically reduced to a finite set by some form of data-driven or regular discretization. In this work, we propose an alternative formulation of multitarget tracking as minimization of a continuous energy.