Brain Cancer

A Multimodal Physics-Informed Neural Network Approach for Mean Radiant Temperature Modeling

Outdoor thermal comfort is a critical determinant of urban livability, particularly in hot desert climates where extreme heat poses challenges to public health, energy consumption, and urban planning. Mean Radiant Temperature ($T_{mrt}$) is a key parameter for evaluating outdoor thermal comfort, especially in urban environments where radiation dynamics significantly impact human thermal exposure...

Generalizable and Explainable Deep Learning for Medical Image Computing: An Overview

Objective. This paper presents an overview of generalizable and explainable artificial intelligence (XAI) in deep learning (DL) for medical imaging, aimed at addressing the urgent need for transparency and explainability in clinical applications. Methodology. We propose to use four CNNs in three medical datasets (brain tumor, skin cancer, and chest x-ray) for medical image classification tasks...

Towards a Multimodal MRI-Based Foundation Model for Multi-Level Feature Exploration in Segmentation, Molecular Subtyping, and Grading of Glioma

Accurate, noninvasive glioma characterization is crucial for effective clinical management. Traditional methods, dependent on invasive tissue sampli...

Joint graphical model estimation using Stein-type shrinkage for fast large scale network inference in scRNAseq data

Graphical modeling is a widely used tool for analyzing conditional dependencies between variables and traditional methods may struggle to capture sh...

Semi-Supervised Learning for Dose Prediction in Targeted Radionuclide: A Synthetic Data Study

Targeted Radionuclide Therapy (TRT) is a modern strategy in radiation oncology that aims to administer a potent radiation dose specifically to cance...

GBT-SAM: Adapting a Foundational Deep Learning Model for Generalizable Brain Tumor Segmentation via Efficient Integration of Multi-Parametric MRI Data

Gliomas are aggressive brain tumors that require accurate imaging-based diagnosis, with segmentation playing a critical role in evaluating morpholog...

Bridging Synthetic-to-Real Gaps: Frequency-Aware Perturbation and Selection for Single-shot Multi-Parametric Mapping Reconstruction

Data-centric artificial intelligence (AI) has remarkably advanced medical imaging, with emerging methods using synthetic data to address data scarci...

NTR-Gaussian: Nighttime Dynamic Thermal Reconstruction with 4D Gaussian Splatting Based on Thermodynamics

Thermal infrared imaging offers the advantage of all-weather capability, enabling non-intrusive measurement of an object's surface temperature. Cons...

Spatiotemporal Variation Assessment and Improved Prediction Of Cyanobacteria Blooms in Lakes Using Improved Machine Learning Model Based on Multivariate Data.

Cyanobacterial blooms in shallow lakes pose a significant threat to aquatic ecosystems and public health worldwide, highlighting the urgent need for a...

NNFit: A Self-Supervised Deep Learning Method for Accelerated Quantification of High-Resolution Short-Echo-Time MR Spectroscopy Datasets.

Purpose To develop and evaluate the performance of NNFit, a self-supervised deep learning method for quantification of high-resolution short-echo-time...

An Attention-Based Deep Neural Network Model to Detect Cis-Regulatory Elements at the Single-Cell Level From Multi-Omics Data.

Cis-regulatory elements (cREs) play a crucial role in regulating gene expression and determining cell differentiation and state transitions. To captur...

Revolutionizing Brain Tumor Detection Using Explainable AI in MRI Images.

Due to the complex structure of the brain, variations in tumor shapes and sizes, and the resemblance between tumor and healthy tissues, the reliable a...

Glioma Classification using Multi-sequence MRI and Novel Wavelets-based Feature Fusion

Glioma, a prevalent and heterogeneous tumor originating from the glial cells, can be differentiated as Low Grade Glioma (LGG) and High Grade Glioma ...

Subclass Classification of Gliomas Using MRI Fusion Technique

Glioma, the prevalent primary brain tumor, exhibits diverse aggressiveness levels and prognoses. Precise classification of glioma is paramount for t...

Diffusion Models for conditional MRI generation

In this article, we present a Latent Diffusion Model (LDM) for the generation of brain Magnetic Resonance Imaging (MRI), conditioning its generation...

Rapid Parameter Inference with Uncertainty Quantification for a Radiological Plume Source Identification Problem

In the event of a nuclear accident, or the detonation of a radiological dispersal device, quickly locating the source of the accident or blast is im...

Differentially private fine-tuned NF-Net to predict GI cancer type

Based on global genomic status, the cancer tumor is classified as Microsatellite Instable (MSI) and Microsatellite Stable (MSS). Immunotherapy is us...

Joint Modelling Histology and Molecular Markers for Cancer Classification

Cancers are characterized by remarkable heterogeneity and diverse prognosis. Accurate cancer classification is essential for patient stratification ...

ARTInp: CBCT-to-CT Image Inpainting and Image Translation in Radiotherapy

A key step in Adaptive Radiation Therapy (ART) workflows is the evaluation of the patient's anatomy at treatment time to ensure the accuracy of the ...

LUND-PROBE -- LUND Prostate Radiotherapy Open Benchmarking and Evaluation dataset

Radiotherapy treatment for prostate cancer relies on computed tomography (CT) and/or magnetic resonance imaging (MRI) for segmentation of target vol...