논문 검색

[PURPOSE] Align with precision radiotherapy campaign of selecting the "right treatment" for "right patient", this study aims to analyze the stratified impact of intrinsic phenotypes and therapeutic interventions on the local recurrence (LR)…

[PURPOSE] To evaluate the prognostic and predictive value of radiomics-based imaging markers in colorectal liver metastasis treated with chemotherapy alone or combined with selective internal radiation therapy in the first-line setting. [M…

Leukemia is a type of blood cancer affecting people of all ages and is the leading cause of death worldwide. The most common form of bone marrow leukemia is acute lymphoblastic leukemia (ALL). Diagnoses often require highly invasive diagnos…

TL;DRDSPA-U-MIL is proposed, an uncertainty-driven dual-selective Gleason Pattern-aware MIL model for patient-level GG prediction that consistently outperforms existing MIL approaches in Gleason GG prediction.

TL;DRThis work proposes a SAM-driven cross prompting framework with adaptive sampling and prompt consistency for semi-supervised medical image segmentation, named CPAC-SAM, and proposes an innovative prototype-guided grid sam…

Gleason grading, the clinical gold standard for prostate cancer assessment, is based on subjective evaluation of glandular architecture, resulting in interobserver variability and limited scalability. This highlights the need for automated …

[PURPOSE] To develop a high-quality four-dimensional magnetic resonance fingerprinting (HQ-4DMRF) framework with temporal low-rank constrained motion compensation for precise tumor motion management in liver radiotherapy. [METHODS] HQ-4DMR…

Patients with breast cancer show substantial heterogeneity in terms of psychological adjustment following diagnosis. We aimed to characterize longitudinal trajectories of quality of life (QoL) and depressive symptoms during the first 18 mon…

Screening and surveillance programs for cancer, such as colorectal cancer (CRC), often yield electronic health records (EHR) of screening time, test results, and covariates. We consider EHR from CRC surveillance of individuals who have a hi…

TL;DRSelf-mutilation lesions in MEG are varied, and their management have benefited from the contribution of microsurgery in developed countries, and it remains problematic in developing countries.

[IMPORTANCE] Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer deaths in the US. Although early detection improves survival, the rarity of the disease has rendered population screening a difficult approach. [OBJECTIVE] T…

TL;DRFlashDeconv is introduced, which combines leverage-score importance sampling with sparse spatial regularization to match top-tier Bayesian accuracy while processing 1.6 million bins in 153 seconds on a standard laptop.

Deep learning for invasive lung adenocarcinoma subtyping remains vulnerable to real-world imaging perturbations. We present a margin consistency framework evaluating 203,226 patches from 143 whole-slide images across five adenocarcinoma sub…

: The integration of multi-omics data, such as genomics and transcriptomics, into artificial intelligence models has advanced precision medicine. However, their clinical applicability remains limited due to model complexity. We integrated D…

Multiparametric Magnetic Resonance Imaging (mpMRI), including T2-weighted imaging (T2), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging is an important technique for the diagnosis of clinically significant pros…

Computational pathology models serve as crucial tools for clinical tasks such as tissue typing, alleviating the burden of manual screening of whole slide images. The stringent ethical regulations on source data, along with agnostic covariat…

BackgroundIn clinical diagnosis, determining the level of malignancy in tumors and differentiating between benign and malignant tumors are common classification challenges. Accurate and early diagnosis is essential for targeted treatment, a…

Tissues are organized through the assembly of diverse cell types into multicellular structures that exhibit hierarchical spatial organization. We present HRCHY-CytoCommunity, a graph neural network framework for identifying multi-level tiss…

Breast cancer diagnosis from histopathology images remains challenging due to two intertwined factors: severe class imbalance, where malignant cases represent a small minority of samples, and the need to integrate discriminative features ac…

This study proposes a clinically driven hybrid segmentation framework for dense breast tissue analysis in mammographic images, addressing persistent challenges associated with intensity inhomogeneity, low-contrast, and complex tumor morphol…