A retinal detachment based strabismus detection through FEDCNN
Ocular strabismus, a common condition in the present generation is an absolute risk factor
for amblyopia and blinding premorbid visual loss. Despite the availability of new optometry …
for amblyopia and blinding premorbid visual loss. Despite the availability of new optometry …
Triple contrastive learning representation boosting for supervised multiclass tasks
X Li, Z Liu, S Liu - Information Processing & Management, 2025 - Elsevier
Supervised contrastive learning is highly effective for extracting sample representations,
thereby enhancing the performance of downstream tasks. However, existing methods …
thereby enhancing the performance of downstream tasks. However, existing methods …
Retinal structure guidance-and-adaption network for early Parkinson's disease recognition based on OCT images
H Shi, J Wei, R Jin, J Peng, X Wang, Y Hu… - … Medical Imaging and …, 2024 - Elsevier
Parkinson's disease (PD) is a leading neurodegenerative disease globally. Precise and
objective PD diagnosis is significant for early intervention and treatment. Recent studies …
objective PD diagnosis is significant for early intervention and treatment. Recent studies …
An attentional mechanism model for segmenting multiple lesion regions in the diabetic retina
C Xu, S He, H Li - Scientific Reports, 2024 - nature.com
Diabetic retinopathy (DR), a leading cause of blindness in diabetic patients, necessitates the
precise segmentation of lesions for the effective grading of lesions. DR multi-lesion …
precise segmentation of lesions for the effective grading of lesions. DR multi-lesion …
Graph confidence intercalibration network for intracranial aneurysm lesion instance segmentation in DSA
Intracranial aneurysm (IA) lesion segmentation is significant for its treatment and prognosis.
Although exiting deep network-based instance methods have good IA lesion segmentation …
Although exiting deep network-based instance methods have good IA lesion segmentation …
Dual-View Pyramid Pooling in Deep Neural Networks for Improved Medical Image Classification and Confidence Calibration
Spatial pooling (SP) and cross-channel pooling (CCP) operators have been applied to
aggregate spatial features and pixel-wise features from feature maps in deep neural …
aggregate spatial features and pixel-wise features from feature maps in deep neural …
Liver fibrosis stage classification in stacked microvascular images based on deep learning
D Miura, H Suenaga, R Hiwatashi, S Mabu - BMC Medical Imaging, 2025 - Springer
Background Monitoring fibrosis in patients with chronic liver disease (CLD) is an important
management strategy. We have already reported a novel stacked microvascular imaging …
management strategy. We have already reported a novel stacked microvascular imaging …
Attention-Guided Residual U-Net with SE Connection and ASPP for Watershed-Based Cell Segmentation in Microscopy Images
Time-lapse microscopy imaging is a crucial technique in biomedical studies for observing
cellular behavior over time, providing essential data on cell numbers, sizes, shapes, and …
cellular behavior over time, providing essential data on cell numbers, sizes, shapes, and …
MM-Retinal V2: Transfer an Elite Knowledge Spark into Fundus Vision-Language Pretraining
R Wu, N Su, C Zhang, T Ma, T Zhou, Z Cui… - arXiv preprint arXiv …, 2025 - arxiv.org
Vision-language pretraining (VLP) has been investigated to generalize across diverse
downstream tasks for fundus image analysis. Although recent methods showcase promising …
downstream tasks for fundus image analysis. Although recent methods showcase promising …