Lung-PNet: an automated deep learning model for the diagnosis of invasive adenocarcinoma in pure ground-glass nodules on chest CT

K Qi, K Wang, X Wang, YD Zhang, G Lin… - American Journal of …, 2024 - ajronline.org
BACKGROUND. Pure ground-glass nodules (pGGNs) on chest CT representing invasive
adenocarcinoma (IAC) warrant lobectomy with lymph node resection. For pGGNs …

Automated placental abruption identification using semantic segmentation, quantitative features, SVM, ensemble and multi-path CNN

V Asadpour, EJ Puttock, D Getahun, MJ Fassett, F **e - Heliyon, 2023 - cell.com
The placenta is a fundamental organ throughout the pregnancy and the fetus' health is
closely related to its proper function. Because of the importance of the placenta, any …

Enhancing deep learning based classifiers with inpainting anatomical side markers (L/R markers) for multi-center trials

KD Kim, K Cho, M Kim, KH Lee, S Lee, SM Lee… - Computer Methods and …, 2022 - Elsevier
Background and objective The protocol for placing anatomical side markers (L/R markers) in
chest radiographs varies from one hospital or department to another. However, the markers …

Prediction of type II diabetes onset with computed tomography and electronic medical records

Y Tang, R Gao, HH Lee, QS Wells, A Spann… - Multimodal Learning for …, 2020 - Springer
Type II diabetes mellitus (T2DM) is a significant public health concern with multiple known
risk factors (eg, body mass index (BMI), body fat distribution, glucose levels). Improved …

Quantitative radiomic features from computed tomography can predict pancreatic cancer up to 36 months before diagnosis

W Chen, Y Zhou, V Asadpour, RA Parker… - Clinical and …, 2023 - journals.lww.com
METHODS: Adults 18 years and older diagnosed with PDAC in 2008–2018 were identified.
Their CT scans 3 months–3 years before the diagnosis date were matched to up to 2 scans …

[HTML][HTML] Deep learning to detect pancreatic cystic lesions on abdominal computed tomography scans: Development and validation study

MM Duh, N Torra-Ferrer, M Riera-Marín, D Cumelles… - JMIR AI, 2023 - ai.jmir.org
Background Pancreatic cystic lesions (PCLs) are frequent and underreported incidental
findings on computed tomography (CT) scans and can evolve to pancreatic cancer—the …

Advancing Medical Image Segmentation: Morphology-Driven Learning with Diffusion Transformer

S Kang, J Song, J Kim - arxiv preprint arxiv:2408.00347, 2024 - arxiv.org
Understanding the morphological structure of medical images and precisely segmenting the
region of interest or abnormality is an important task that can assist in diagnosis. However …

[HTML][HTML] Machine Learning-Driven Radiomics Analysis for Distinguishing Mucinous and Non-Mucinous Pancreatic Cystic Lesions: A Multicentric Study

N Torra-Ferrer, MM Duh, Q Grau-Ortega… - Journal of …, 2025 - mdpi.com
The increasing use of high-resolution cross-sectional imaging has significantly enhanced
the detection of pancreatic cystic lesions (PCLs), including pseudocysts and neoplastic …

A convolutional neural network-based auto-segmentation pipeline for breast cancer imaging

LJH Leow, AB Azam, HQ Tan, WL Nei, Q Cao, L Huang… - Mathematics, 2024 - mdpi.com
Medical imaging is crucial for the detection and diagnosis of breast cancer. Artificial
intelligence and computer vision have rapidly become popular in medical image analyses …

[HTML][HTML] WindowNet: Learnable Windows for Chest X-ray Classification

A Wollek, S Hyska, B Sabel, M Ingrisch, T Lasser - Journal of Imaging, 2023 - mdpi.com
Public chest X-ray (CXR) data sets are commonly compressed to a lower bit depth to reduce
their size, potentially hiding subtle diagnostic features. In contrast, radiologists apply a …