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Skin Lesion Classification Based on Involution Neural Networks with Triplet++ Attention Generator
Skin is the biggest organ in the human body that protects us from hurt and supports the function of material exchange. Most skin cancers develop from skin lesions which cannot avoid in our daily life. To diagnose skin cancer, now we still rely on the ...
Ocular Disease Recognition and Classification using TripleGAN
Ocular diseases pose significant challenges in the field of ophthalmology. The accurate classification of fundus images depicting various ocular diseases plays a vital role in early diagnosis and effective treatment planning. However, medical datasets ...
A Transformer-based Method for Skin Fungi Identification from Fluorescent Images
Due to the increasing number of patients with impaired immune function and the widespread use of broad-spectrum antibiotics, the rate of fungal infections is rising and invasive fungal infections (IFD) have become one of the major causes of death. ...
Edge Computing-Based Cloud Platform for Snakebite Assisted Diagnosis
Snakebite is a major global public health problem, with more than 5 million snakebite victims recorded each year. Timely diagnosis and appropriate treatment of snakebite are the keys to preventing serious complications and improving the patient’s ...
Classification of A Pressing Movement by Background Removed Single- photon Calcium Image Sequences
Calcium imaging, with its capability to record hundreds or even thousands of neurons simultaneously, has been widely applied in the fields of neuroscience and neural decoding. Current neural decoding experiments utilizing calcium imaging depend on ...
An Automatic Classification Framework using Multi-Modal Deep Learning for Lung Diseases
Disease identification across multiple modalities remains a challenging task. Recent research has explored early, automatic disease prediction using single modality inputs and computer vision with deep learning techniques. In this study, we introduce ...
ADHD Classification Based on fMRI Spatial-Temporal Features Using Monofractal and Multifractal Dimensions
Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common mental disorders worldwide. Since it is associated with abnormal fuctional connectivity of brain activity, current researches tend to extract biomarkers and construct objective ...
An Investigation of Segment Anything Model (SAM) on Uterus Segmentation
Highly development of language-image models makes prompt-driven accurate segmentation become possible. Segment Anything Model (SAM) has recently made a breakthrough in zero-shot image segmentation, using an unprecedentedly large dataset to train a ...
Res BCDU-SCB Net: A Lung CT Image Segmentation based on SC-BLSTM
Due to the unique physiological structure of human lung tissue, segmentation of the lung parenchymal regions is a very challenging task. Traditional image segmentation methods have certain limitations on practical applications. Therefore, lung tissue ...
Enhanced U2Net Framework for Pulmonary Airway Segmentation in CT
Given the intricate three-dimensional structure and variable density of lung tissue, accurate airway segmentation remains a challenging task. This study proposes a method rooted in an enhanced U2-Net t architecture that excels in identifying small ...
Diagnosis of Thyroid Nodule Based on Multi-Scale Se-Segnet and Resnet50
Thyroid nodule is a common chronic endocrine system disease, which may deteriorate into thyroid cancer without treatment. However, due to the distribution of many blood vessels, nerves and organs near the thyroid, the clarity of ultrasonic image is poor,...
An Efficient Tongue Segmentation Method Using Synthetic Data Based on Fourier Transform and FASSP
Tongue segmentation is a key step to realize the intelligent tongue diagnosis of traditional Chinese medicine. The segmentation based on deep neural networks has achieved good results with a large amount of data with pixel-level annotation. But it is ...
Tumor Segmentation in Weakly Paired Anatomical and Functional MRI images with Multimodal Information Fusion
Multimodal magnetic resonance imaging (MRI) contains complementary information in anatomical and functional images that help the accurate diagnosis and treatment evaluation of lung cancers. Accurately segmenting tumor regions in each modality can help ...
The Sitting and lying Posture Recognition via Pressure Information based on Unconstrained Flexible Pressure Sensor
For detecting sleeping and sitting postures, a system based on unrestrained flexible pressure sensor is designed and proposed. The large-area capacitive pressure sensor, which composited by 64-row and 32-column, is designed to capture posture pressure ...
ESNet: An Effective and Simple Network for Sleep Stage Classification Based on Polysomnography
Sleep is essential for human life. Automatic sleep stage classification based on polysomnography (PSG) has attracted extensive attention recently, which is fundamental for the diagnosis of sleep diseases. Single-channel sleep staging methods usually ...
Psychological Stress Assessment Method Based on Learning Using Privileged Information Framework
At present, research mainly uses single modal and multimodal physiological signals to identify human psychological states, but these methods generally have the drawbacks of low evaluation accuracy, poor applicability, and weak effectiveness. To address ...
RARPL6: Development of A Clinical Dataset for Surgical Workflow Recognition from Robot-Assisted Radical Prostatectomy with Lymphadenectomy
- Ziyang Chen,
- Alice Pierini,
- Eleonora Pollini,
- Raffaella Salama,
- Theo Pauvel,
- Elena Lievore,
- Giancarlo Ferrigno,
- Elena De Momi
Surgical workflow recognition has attracted widespread attention in robot-assisted surgery since it can provide surgical context information automatically, which releases the cognitive burden of the surgeons and allows more appropriate surgical ...
H3S: A Hospital Staff Sign-in System Based on Face Recognition
Abstract: There are many problems in traditional hospital staff sign-in systems, such as low efficiency, time required to obtain result statistics, and fraud. A system based on face recognition is a very promising strategy. In 2022, the highest accuracy ...
Research on Pose Recognition Based on Openpose Bone Point Labeling
Nowadays, teenagers and children have many problems with poor posture. In order to timely and accurately identify the health problems of teenagers' posture, this study proposes to use the bottom-up Openpose bone point marking technology based on deep ...
Electric Field Simulation for Tumor Treating Fields Using FEM: An Open Source and Easy-To-Use Implementation
Tumor Treating Fields (TTFields) therapy is a promising cancer treatment technique that inhibits tumor cell proliferation by applying alternating electric fields. Numerical simulations of TTFields electric fields based on realistic models have been ...
Multifactorial Influence on the Dynamic Characteristics of Human Lumbar Vertebrae
This paper focuses on the human lumbar vertebrae and explores how changes in the position of the center of gravity of the upper body and tissue material properties of human lumbar vertebrae impact its dynamic characteristics. The modal response ...
Index Terms
- Proceedings of the 2023 8th International Conference on Biomedical Signal and Image Processing