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View article: MPF-Net: A multi-scale feature learning network enhanced by prior knowledge integration for medical image segmentation
MPF-Net: A multi-scale feature learning network enhanced by prior knowledge integration for medical image segmentation Open
s: Precise delineation of medical images plays a crucial role in advancing automated diagnostic systems and therapeutic strategy development. Despite the advancements in traditional CNN-based segmentation methods, they encounter significan…
View article: A multimodal fusion network based on variational autoencoder for distinguishing SCLC brain metastases from NSCLC brain metastases
A multimodal fusion network based on variational autoencoder for distinguishing SCLC brain metastases from NSCLC brain metastases Open
Background Distinguishing small cell lung cancer brain metastases from non‐small cell lung cancer brain metastases in MRI sequence images is crucial for the accurate diagnosis and treatment of lung cancer brain metastases. Multi‐MRI modali…
View article: A multi-stage deep learning network toward multi-classification of polyps in colorectal images
A multi-stage deep learning network toward multi-classification of polyps in colorectal images Open
Accurate classification of colorectal polyps (CRPs) is critical for the early diagnosis and treatment of colorectal cancer (CRC). This paper presents an efficient deep learning method specifically developed to enhance the accuracy of CRPs …
View article: A study on the application of radiomics based on cardiac MR non-enhanced cine sequence in the early diagnosis of hypertensive heart disease
A study on the application of radiomics based on cardiac MR non-enhanced cine sequence in the early diagnosis of hypertensive heart disease Open
Background The prevalence of hypertensive heart disease (HHD) is high and there is currently no easy way to detect early HHD. Explore the application of radiomics using cardiac magnetic resonance (CMR) non-enhanced cine sequences in diagno…
View article: Use of MRI Radiomics Models in Evaluating the Low HER2 Expression inBreast Cancer
Use of MRI Radiomics Models in Evaluating the Low HER2 Expression inBreast Cancer Open
Objective: To investigate the magnetic resonance imaging (MRI) radiomics models in evaluating the human epidermal growth factor receptor 2(HER2) expression in breast cancer. Materials and Methods: The MRI data of 161 patients with invasive…
View article: Using MsfNet to Predict the ISUP Grade of Renal Clear Cell Carcinoma in Digital Pathology Images
Using MsfNet to Predict the ISUP Grade of Renal Clear Cell Carcinoma in Digital Pathology Images Open
Clear cell renal cell carcinoma (ccRCC) represents the most frequent form of renal cell carcinoma (RCC), and accurate International Society of Urological Pathology (ISUP) grading is crucial for prognosis and treatment selection.This study …
View article: Using machine learning-based radiomics to differentiate between glioma and solitary brain metastasis from lung cancer and its subtypes
Using machine learning-based radiomics to differentiate between glioma and solitary brain metastasis from lung cancer and its subtypes Open
Objective To establish a machine learning-based radiomics model to differentiate between glioma and solitary brain metastasis from lung cancer and its subtypes, thereby achieving accurate preoperative classification. Materials and methods …
View article: Robust vessel segmentation in laser speckle contrast images based on semi-weakly supervised learning
Robust vessel segmentation in laser speckle contrast images based on semi-weakly supervised learning Open
Objective. The goal of this study is to develop a robust semi-weakly supervised learning strategy for vessel segmentation in laser speckle contrast imaging (LSCI), addressing the challenges associated with the low signal-to-noise ratio, sm…
View article: URNet: System for recommending referrals for community screening of diabetic retinopathy based on deep learning
URNet: System for recommending referrals for community screening of diabetic retinopathy based on deep learning Open
Diabetic retinopathy (DR) will cause blindness if the detection and treatment are not carried out in the early stages. To create an effective treatment strategy, the severity of the disease must first be divided into referral-warranted dia…
View article: Multi-Classification of Polyps in Colonoscopy Images Based on an Improved Deep Convolutional Neural Network
Multi-Classification of Polyps in Colonoscopy Images Based on an Improved Deep Convolutional Neural Network Open
Achieving accurate classification of colorectal polyps during colonoscopy can avoid unnecessary endoscopic biopsy or resection. This study aimed to develop a deep learning model that can automatically classify colorectal polyps histologica…
View article: Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution
Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution Open
The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR…
View article: MPFracNet: A Deep Learning Algorithm for Metacarpophalangeal Fracture Detection with Varied Difficulties
MPFracNet: A Deep Learning Algorithm for Metacarpophalangeal Fracture Detection with Varied Difficulties Open
Due to small size and high occult, metacarpophalangeal fracture diagnosis displays a low accuracy in terms of fracture detection and location in X-ray images. To efficiently detect metacarpophalangeal fractures on X-ray images as the secon…
View article: A Dual-Selective Channel Attention Network for Osteoporosis Prediction in Computed Tomography Images of Lumbar Spine
A Dual-Selective Channel Attention Network for Osteoporosis Prediction in Computed Tomography Images of Lumbar Spine Open
Osteoporosis is a common systemic bone disease with insidious onset and low treatment efficiency. Once it occurs, it will increase bone fragility and lead to fractures. Computed tomography (CT) is a non-invasive medical examination method …
View article: [Research status and prospect of artificial intelligence technology in the diagnosis of urinary system tumors].
[Research status and prospect of artificial intelligence technology in the diagnosis of urinary system tumors]. Open
With the rapid development of artificial intelligence technology, researchers have applied it to the diagnosis of various tumors in the urinary system in recent years, and have obtained many valuable research results. The article sorted th…
View article: Detection and localization of hand fractures based on GA_Faster R-CNN
Detection and localization of hand fractures based on GA_Faster R-CNN Open
X-ray imaging is the primary diagnostic tool for clinical diagnosis of suspected fracture. Hand fracture (HF) is a world-leading health problem for children, adolescents and the elderly. A missed diagnosis of hand fracture on radiography m…
View article: Automatic detection and segmentation of adenomatous colorectal polyps during colonoscopy using Mask R-CNN
Automatic detection and segmentation of adenomatous colorectal polyps during colonoscopy using Mask R-CNN Open
Colorectal cancer (CRC) is one of the main alimentary tract system malignancies affecting people worldwide. Adenomatous polyps are precursors of CRC, and therefore, preventing the development of these lesions may also prevent subsequent ma…
View article: Design of Home-Based Elderly Health Care System
Design of Home-Based Elderly Health Care System Open
In this paper, we designed a home-based elderly care system, which consists of three parts: Equipment for Health detection, Monitoring cloud and Mobile user terminal.Combining intelligent sensing technology, GPRS wireless communication, Et…
View article: Frequent Patterns Algorithm of Biological Sequences based on Pattern Prefix-tree
Frequent Patterns Algorithm of Biological Sequences based on Pattern Prefix-tree Open
In the application of bioinformatics, the existing algorithms cannot be directly and efficiently implement sequence pattern mining. Two fast and efficient biological sequence pattern mining algorithms for biological single sequence and mul…
View article: Computed Tomography Beam Hardening Correction Based on Non-linear Segmentation
Computed Tomography Beam Hardening Correction Based on Non-linear Segmentation Open
This paper aims to eliminate the hardening artifacts in computed tomography (CT) images caused by the polychromatic X-ray spectrum. To this end, a polynomial fitting correction method using non-liner segmentation method was developed throu…
View article: Temperature Characteristics and Compensation of PET Detector
Temperature Characteristics and Compensation of PET Detector Open
The detector is the core component of PET. Temperature of the detector has a significant impact on the quality of PET image. The operating temperature of the machine can result in reduced spatial resolution, declining image quality and dia…
View article: Dynamic modulation of the perceptual load on microsaccades during a selective spatial attention task
Dynamic modulation of the perceptual load on microsaccades during a selective spatial attention task Open
Selective spatial attention enhances task performance at restricted regions within the visual field. The magnitude of this effect depends on the level of attentional load, which determines the efficiency of distractor rejection. Mechanisms…