Thiara Sana Ahmed

MARVEL: Universal Murray's Law-informed Vessel Tree Segmentation and Topology Estimation

Yi Zhou, Thiara Sana Ahmed, Jacqueline Chua, Meng Wang et autres

Vascular circulation follows fundamental biophysical principles that optimize mass transport and metabolic energy expenditure, which can be effectively modeled by Murray's law. However, contemporary deep learning methods for vascular segmentation often neglect these biophysical constraints. This leads to physiologically implausible branching and …

MARVEL: Universal Murray's Law-informed Vessel Tree Segmentation and Topology Estimation

Yi Zhou, Thiara Sana Ahmed, Jacqueline Chua, Meng Wang et autres

Vascular circulation follows fundamental biophysical principles that optimize mass transport and metabolic energy expenditure, which can be effectively modeled by Murray's law. However, contemporary deep learning methods for vascular segmentation often neglect these biophysical constraints. This leads to physiologically implausible branching and …

AMeta-FD: Adversarial Meta-learning for Few-shot retinal OCT image Despeckling

Yi Zhou, Tao Peng, Thiara Sana Ahmed, Fei Shi et autres

cn, sg (code pays fourni par la source)

Masked Vascular Structure Segmentation and Completion in Retinal Images

Yi Zhou, Thiara Sana Ahmed, Meng Wang, Eric A. Newman et autres

Early retinal vascular changes in diseases such as diabetic retinopathy often occur at a microscopic level. Accurate evaluation of retinal vascular networks at a micro-level could significantly improve our understanding of angiopathology and potentially aid ophthalmologists in disease assessment and management. Multiple …

sg, us, fr (code pays fourni par la source)

On the Use of Machine Learning for Estimation of Complex Graph Networks and Flows, With Application to Retina Vasculature and Glaucoma Diagnostics

George Barbastathis, Sandip Mondal, Thiara Sana Ahmed, Bingyao Tan et autres

We show that graph connectivity and the associated flow properties are mapped onto spatial and temporal fluctuations in the far field. The autocorrelation functions are processed by unsupervised and supervised algorithms to invert this mapping. Full-text article not available; see video presentation

us, sg, cn (code pays fourni par la source)

On the use of Machine Learning for Quantifying Complex Processes, With Application to Retina Vasculature and Glaucoma Diagnostics

George Barbastathis, Sandip Mondal, Thiara Sana Ahmed, BY Tan et autres

We investigate the mapping between flows on complex graphs, such as retina vasculature, and spatial-temporal flucturations in the far field. Unsupervised and supervised learning algorithms can be used to invert these maps and obtain quantitative information about connectivity and blood flow. Full-text …

us, sg, cn (code pays fourni par la source)

Machine Learning-Aided At-Line Detection of Bacterial marker NA for Cell Manufacturing

Jiayi Huang, Thiara Sana Ahmed, Maciej Barański, Elizabeth Lee et autres

We show a machine learning-aided UV spectroscopy-based method using aseptic instrumentation to detect metabolite NA, a marker of microbial contamination. This potentially enables rapid, at-line microbial contamination detection in cell manufacturing.

sg, us (code pays fourni par la source)