Oncology/Hematology

AI-assisted Early Detection of Pancreatic Ductal Adenocarcinoma on Contrast-enhanced CT

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common and aggressive types of pancreatic cancer. However, due to the lack of early and disease-specific symptoms, most patients with PDAC are diagnosed at an advanced disease stage. Consequently, early PDAC detection is crucial for improving patients' quality of life and expanding treatment options. In this work, we develop a coarse-to-...

Multi-Modal Mamba Modeling for Survival Prediction (M4Survive): Adapting Joint Foundation Model Representations

Accurate survival prediction in oncology requires integrating diverse imaging modalities to capture the complex interplay of tumor biology. Traditional single-modality approaches often fail to leverage the complementary insights provided by radiological and pathological assessments. In this work, we introduce M4Survive (Multi-Modal Mamba Modeling for Survival Prediction), a novel framework that ...

Fine-tuning Vision Language Models with Graph-based Knowledge for Explainable Medical Image Analysis

Accurate staging of Diabetic Retinopathy (DR) is essential for guiding timely interventions and preventing vision loss. However, current staging mod...

DAMM-Diffusion: Learning Divergence-Aware Multi-Modal Diffusion Model for Nanoparticles Distribution Prediction

The prediction of nanoparticles (NPs) distribution is crucial for the diagnosis and treatment of tumors. Recent studies indicate that the heterogene...

Deformable Registration Framework for Augmented Reality-based Surgical Guidance in Head and Neck Tumor Resection

Head and neck squamous cell carcinoma (HNSCC) has one of the highest rates of recurrence cases among solid malignancies. Recurrence rates can be red...

Segmentation-Guided CT Synthesis with Pixel-Wise Conformal Uncertainty Bounds

Accurate dose calculations in proton therapy rely on high-quality CT images. While planning CTs (pCTs) serve as a reference for dosimetric planning,...

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 pu...

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,...

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...

From Slices to Sequences: Autoregressive Tracking Transformer for Cohesive and Consistent 3D Lymph Node Detection in CT Scans

Lymph node (LN) assessment is an essential task in the routine radiology workflow, providing valuable insights for cancer staging, treatment plannin...

Modeling HIF-ILK Interaction Using Continuous Petri Nets

Oxygen concentration in tumor micro-environment is a well-established signal that can induce aggressive cancer behaviour. In particular, low oxygen ...

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...

Interactive Tumor Progression Modeling via Sketch-Based Image Editing

Accurately visualizing and editing tumor progression in medical imaging is crucial for diagnosis, treatment planning, and clinical communication. To...

Predicting early recurrence of hepatocellular carcinoma after thermal ablation based on longitudinal MRI with a deep learning approach.

BACKGROUND: Accurate prediction of early recurrence (ER) is essential to improve the prognosis of patients with hepatocellular carcinoma (HCC) underwe...

Multimodal AI-driven Biomarker for Early Detection of Cancer Cachexia

Cancer cachexia is a multifactorial syndrome characterized by progressive muscle wasting, metabolic dysfunction, and systemic inflammation, leading ...

LSA: Latent Style Augmentation Towards Stain-Agnostic Cervical Cancer Screening

The deployment of computer-aided diagnosis systems for cervical cancer screening using whole slide images (WSIs) faces critical challenges due to do...

Task-oriented Uncertainty Collaborative Learning for Label-Efficient Brain Tumor Segmentation

Multi-contrast magnetic resonance imaging (MRI) plays a vital role in brain tumor segmentation and diagnosis by leveraging complementary information...

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...

Big data analytics and machine learning in hematology: Transformative insights, applications and challenges.

The integration of big data analytics and machine learning (ML) into hematology has ushered in a new era of precision medicine, offering transformativ...

PathoPainter: Augmenting Histopathology Segmentation via Tumor-aware Inpainting

Tumor segmentation plays a critical role in histopathology, but it requires costly, fine-grained image-mask pairs annotated by pathologists. Thus, s...