Siameses

The purpose of this study is to determine how photo biomodulation therapy utilizing infrared diode laser irradiation (975.2 nm) affects the gonadal maturity level (GML) of male Siamese catfish (Pan-gasianodon hypothalamus). The interest in applying laser therapy in medicine and dentistry has remarkably increased in the last decade. Different types of lasers are available, and their usage is well-defined by different parameters, such as wavelength, energy density, power output, duration of radiation, power density and radiation mode...

Face verification, crucial for identity authentication and access control in our digital society, faces significant challenges when comparing images taken in diverse environments, which vary in terms of distance, angle, and lighting conditions. These disparities often lead to decreased accuracy due to significant resolution changes. This paper introduces an adaptive face verification solution tailored for diverse conditions, particularly focusing on Unmanned Aerial Vehicle (UAV)-based public safety applications...

AA-amyloidosis in Siamese and Oriental shorthair cats is a lethal condition in which amyloid deposits accumulate systemically, especially in the liver and the thyroid gland. The age at death of affected cats varies between one and seven years. A previous study indicated a complex mode of inheritance involving a major locus. In the present study, we performed a multi-locus genome-wide association study (GWAS) using five methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB and ISIS EM-BLASSO) to identify variants associated with AA-amyloidosis in Siamese/Oriental cats...

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Alzheimer's disease (AD) is a degenerative neurologic condition that results in the deterioration of several brain processes (e.g. memory loss). The most notable physical alteration in AD is the impairment of brain cells. An accurate examination of brain pictures may help to find the disease earlier because early diagnosis is crucial to enhancing patient care and treatment outcomes. Therefore, an easy and error-free system for AD diagnosis has recently received much research attention. Conventional image processing techniques sometimes cannot observe the significant features...

BACKGROUND: Siamese network (SN) using longitudinal DCE-MRI for pathologic complete response (pCR) identification lack a unified approach to phases selection. PURPOSE: To identify pCR in early-stage NAC, using SN with longitudinal DCE-MRI and introducing IPS for phases selection. STUDY TYPE: Multicenter, longitudinal. POPULATION: Center A: 162 female patients (50.63 ± 8.41 years) divided 7:3 into training and internal validation cohorts...

Conjoined twins (CTs), popularly referred to as Siamese twins, are a rare anomaly due to monochorionic and monoamniotic twin pregnancies. Dicephalus dibrachius dipus, a type of parapagus conjoined twin which is characterized by possessing two arms, two legs, a single trunk and two heads, epidemiologically, is an even rarer occurrence of CTs. In this article, a rare, well-preserved anatomical specimen of a dicephalus dibrachius dipus conjoined twin is presented. This study was conducted in a specimen which is part of the collection of the Embryology Museum of the institution by donation and approved by the Research Ethics Committee (REC)...

Systemic treatment is a main way for pancreas cancer patients that are ineligible for surgery. A subgroup of patients showed good response to systemic treatment and the rest received limited benefits. CT images provide a non-invasive way to assess the treatment response. Alternative non-image methods include radiology analysis, tumor marker analysis and combination analysis. To combine the image and non-image data, we propose the Siamese Delta Network with Multimodality Fusion (SDN-MF) to predict systemic treatment response in an end-to-end way...

Hyperspectral images provide a wealth of spectral and spatial information, offering significant advantages for the purpose of tracking objects. However, Siamese trackers are unable to fully exploit spectral features due to the limited number of hyperspectral videos. The high-dimensional nature of hyperspectral images complicates the model training process. In order to address the aforementioned issues, this article proposes a hyperspectral object tracking (HOT) algorithm callled SiamPKHT, which leverages the SiamCAR model by incorporating pyramid shuffle attention (PSA) and knowledge distillation (KD)...

The growing on-board processing capabilities have led to more complex sensor configurations, enabling autonomous car prototypes to expand their operational scope. Nowadays, the joint use of LiDAR data and multiple cameras is almost a standard and poses new challenges for existing multi-modal perception pipelines, such as dealing with contradictory or redundant detections caused by inference on overlapping images. In this paper, we address this last issue in the context of sequential schemes like F-PointNets, where object candidates are obtained in the image space, and the final 3D bounding box is then inferred from point cloud information...

Barrier islands are vital dynamic landforms that not only host ecological resources but often protect coastal ecosystems from storm damage. The Waisanding Barrier (WSDB) in Taiwan has suffered from continuous beach erosion in recent decades. In this study, we developed a SiamUnet network compared to three basic DeepUnet networks with different image sizes to effectively detect barrier waterlines from 207 high-resolution satellite images. The evolution of the barrier waterline shape is obtained to present two special morphologic changes at the southern end and the evolution of the entire waterline...

Colorectal cancer is a leading cause of cancer-related deaths globally. In recent years, the use of convolutional neural networks in computer-aided diagnosis (CAD) has facilitated simpler detection of early lesions like polyps during real-time colonoscopy. However, the majority of existing techniques require a large training dataset annotated by experienced experts. To alleviate the laborious task of image annotation and utilize the vast amounts of readily available unlabeled colonoscopy data to further improve the polyp detection ability, this study proposed a novel self-supervised representation learning method called feature pyramid siamese networks (FPSiam)...

Identical twins joined in utero are called conjoined twins. They are also called "Siamese twins." It is one of the uncommon variants of twin pregnancy. Our case report aims to demonstrate the significance of prenatal diagnosis and evaluation of conjoined twins due to the increased risk of perinatal morbidity and death. Early prenatal diagnosis and assessment of the degree of joining provide an opportunity for parents to decide whether to continue the pregnancy.

Prescription data is an important focus and breakthrough in the study of clinical treatment rules, and the complex multidimensional relationships between Traditional Chinese medicine (TCM) prescription data increase the difficulty of extracting knowledge from clinical data. This paper proposes a complex prescription recognition algorithm (MTCMC) based on the classification and matching of TCM prescriptions with classical prescriptions to identify the classical prescriptions contained in the prescriptions and provide a reference for mining TCM knowledge...

Siamese tracking has witnessed tremendous progress in tracking paradigm. However, its default box estimation pipeline still faces a crucial inconsistency issue, namely, the bounding box decided by its classification score is not always best overlapped with the ground truth, thus harming performance. To this end, we explore a novel simple tracking paradigm based on the intersection over union (IoU) value prediction. To first bypass this inconsistency issue, we propose a concise target state predictor termed IoUformer, which instead of default box estimation pipeline directly predicts the IoU values related to tracking performance metrics...

Drug failure during experimental procedures due to low bioactivity presents a significant challenge. To mitigate this risk and enhance compound bioactivities, predicting bioactivity classes during lead optimization is essential. The existing studies on structure-activity relationships have highlighted the connection between the chemical structures of compounds and their bioactivity. However, these studies often overlook the intricate relationship between drugs and bioactivity, which encompasses multiple factors beyond the chemical structure alone...

BACKGROUND: Fetal brain magnetic resonance imaging (MRI)-based gestational age prediction has been widely used to characterize normal fetal brain development and diagnose congenital brain malformations. PURPOSE: The uncertainty of fetal position and external interference leads to variable localization and direction of the fetal brain. In addition, pregnant women typically concentrate on receiving MRI scans during the fetal anomaly scanning week, leading to an imbalanced distribution of fetal brain MRI data...

OBJECTIVE: Accurate vocal cord leukoplakia classification is instructive for clinical diagnosis and surgical treatment. This article introduces a reliable very deep Siamese network for accurate vocal cord leukoplakia classification. STUDY DESIGN: A study of a classification network based on a retrospective database. SETTING: Academic university and hospital. METHODS: The white light image datasets of vocal cord leukoplakia used in this article were classified into 6 classes: normal tissues, inflammatory keratosis, mild dysplasia, moderate dysplasia, severe dysplasia, and squamous cell carcinoma...

Learning representations from unlabeled time series data is a challenging problem. Most existing self-supervised and unsupervised approaches in the time-series domain fall short in capturing low-and high-frequency features at the same time. As a result, the generalization ability of the learned representations remains limited. Furthermore, some of these methods employ large-scale models like transformers or rely on computationally expensive techniques such as contrastive learning. To tackle these problems, we propose a noncontrastive self-supervised learning (SSL) approach that efficiently captures low-and high-frequency features in a cost-effective manner...

BACKGROUND: Although Chlamydia sp. causes widespread disease outbreaks in juvenile crocodiles in Thailand, data regarding the epidemiology, and risk factors of such infections are limited. The aim of this study was to investigate the prevalence and possible risk factors associated with Chlamydia sp. infections on Siamese crocodile (Crocodylus siamensis) farms in Thailand. A cross-sectional study was conducted from July to December 2019. Samples were collected from 40 farms across six regions in Thailand...