Lymphoma

Personalizing Federated Learning for Hierarchical Edge Networks with Non-IID Data

Accommodating edge networks between IoT devices and the cloud server in Hierarchical Federated Learning (HFL) enhances communication efficiency without compromising data privacy. However, devices connected to the same edge often share geographic or contextual similarities, leading to varying edge-level data heterogeneity with different subsets of labels per edge, on top of device-level heterogen...

Synthetic CT Generation from Time-of-Flight Non-Attenutaion-Corrected PET for Whole-Body PET Attenuation Correction

Positron Emission Tomography (PET) imaging requires accurate attenuation correction (AC) to account for photon loss due to tissue density variations. In PET/MR systems, computed tomography (CT), which offers a straightforward estimation of AC is not available. This study presents a deep learning approach to generate synthetic CT (sCT) images directly from Time-of-Flight (TOF) non-attenuation cor...

An ensemble deep learning approach to detect tumors on Mohs micrographic surgery slides

Mohs micrographic surgery (MMS) is the gold standard technique for removing high risk nonmelanoma skin cancer however, intraoperative histopathologi...

PathOrchestra: A Comprehensive Foundation Model for Computational Pathology with Over 100 Diverse Clinical-Grade Tasks

The complexity and variability inherent in high-resolution pathological images present significant challenges in computational pathology. While path...

Explicit non-free tensors

Free tensors are tensors which, after a change of bases, have free support: any two distinct elements of its support differ in at least two coordina...

A weakly-supervised deep learning model for fast localisation and delineation of the skeleton, internal organs, and spinal canal on Whole-Body Diffusion-Weighted MRI (WB-DWI)

Background: Apparent Diffusion Coefficient (ADC) values and Total Diffusion Volume (TDV) from Whole-body diffusion-weighted MRI (WB-DWI) are recogni...

A Prototype-Guided Coarse Annotations Refining Approach for Whole Slide Images

The fine-grained annotations in whole slide images (WSIs) show the boundaries of various pathological regions. However, generating such detailed ann...

Whole-Body Image-to-Image Translation for a Virtual Scanner in a Healthcare Digital Twin

Generating positron emission tomography (PET) images from computed tomography (CT) scans via deep learning offers a promising pathway to reduce radi...

Smoothing ADMM for Non-convex and Non-smooth Hierarchical Federated Learning

This paper presents a hierarchical federated learning (FL) framework that extends the alternating direction method of multipliers (ADMM) with smooth...

Hybrid Deep Reinforcement Learning for Radio Tracer Localisation in Robotic-assisted Radioguided Surgery

Radioguided surgery, such as sentinel lymph node biopsy, relies on the precise localization of radioactive targets by non-imaging gamma/beta detecto...

Towards Scalable and Cross-Lingual Specialist Language Models for Oncology

Clinical oncology generates vast, unstructured data that often contain inconsistencies, missing information, and ambiguities, making it difficult to...

Dynamic PET Image Reconstruction via Non-negative INR Factorization

The reconstruction of dynamic positron emission tomography (PET) images from noisy projection data is a significant but challenging problem. In this...

Physics-Informed Residual Neural Ordinary Differential Equations for Enhanced Tropical Cyclone Intensity Forecasting

Accurate tropical cyclone (TC) intensity prediction is crucial for mitigating storm hazards, yet its complex dynamics pose challenges to traditional...

Graph neural networks for single-cell omics data: a review of approaches and applications.

Rapid advancement of sequencing technologies now allows for the utilization of precise signals at single-cell resolution in various omics studies. How...

FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis.

Single-cell multi-omics technologies have revolutionized the study of cell states and functions by simultaneously profiling multiple molecular layers ...

Explainable Classifier for Malignant Lymphoma Subtyping via Cell Graph and Image Fusion

Malignant lymphoma subtype classification directly impacts treatment strategies and patient outcomes, necessitating classification models that achie...

A Transfer Framework for Enhancing Temporal Graph Learning in Data-Scarce Settings

Dynamic interactions between entities are prevalent in domains like social platforms, financial systems, healthcare, and e-commerce. These interacti...

FLStore: Efficient Federated Learning Storage for non-training workloads

Federated Learning (FL) is an approach for privacy-preserving Machine Learning (ML), enabling model training across multiple clients without central...

AMPLE: Event-Driven Accelerator for Mixed-Precision Inference of Graph Neural Networks

Graph Neural Networks (GNNs) have recently gained attention due to their performance on non-Euclidean data. The use of custom hardware architectures...

Asymptotics of Non-Convex Generalized Linear Models in High-Dimensions: A proof of the replica formula

The analytic characterization of the high-dimensional behavior of optimization for Generalized Linear Models (GLMs) with Gaussian data has been a ce...