Clipath: Fine-tune clip with visual feature fusion for pathology image analysis towards minimizing data collection efforts
Abstract Contrastive Language-Image Pre-training (CLIP) has shown its ability to learn
distinctive visual representations and generalize to various downstream vision tasks …
distinctive visual representations and generalize to various downstream vision tasks …
Implicit anatomical rendering for medical image segmentation with stochastic experts
Integrating high-level semantically correlated contents and low-level anatomical features is
of central importance in medical image segmentation. Towards this end, recent deep …
of central importance in medical image segmentation. Towards this end, recent deep …
High-throughput digital quantification of Alzheimer disease pathology and associated infrastructure in large autopsy studies
High-throughput digital pathology offers considerable advantages over traditional
semiquantitative and manual methods of counting pathology. We used brain tissue from 5 …
semiquantitative and manual methods of counting pathology. We used brain tissue from 5 …
Preanalytic variable effects on segmentation and quantification machine learning algorithms for amyloid-β analyses on digitized human brain slides
LC Oliveira, Z Lai, D Harvey, K Nzenkue… - … of Neuropathology & …, 2023 - academic.oup.com
Computational machine learning (ML)-based frameworks could be advantageous for
scalable analyses in neuropathology. A recent deep learning (DL) framework has shown …
scalable analyses in neuropathology. A recent deep learning (DL) framework has shown …
Fast Meta Failure Recovery for Federated Meta-Learning
B Delliquadri, C Wang, S Chen, Z Li… - … Conference on Big …, 2023 - ieeexplore.ieee.org
In recent years, the field of distributed deep learning within the Internet of Things (IoT) or the
edge has experienced exponential growth. Federated meta-learning has emerged as a …
edge has experienced exponential growth. Federated meta-learning has emerged as a …