Challenges to the management of oncologic theranostics clinical trials: recommendations for the conduct of theranostics trials at investigational sites [0.03%]
肿瘤治疗诊断学临床试验管理的挑战：关于在研发现场开展治疗诊断学试验的指导意见
Nicholas P Gruszauskas,Joseph Steiner,Krista Dillingham
Nicholas P Gruszauskas
Purpose: Advancements in radionuclide imaging and therapy techniques have created a groundswell of enthusiasm in the recently designated field of theranostics. This has increased the need for facilities that are able to p...
Deep learning-based mediastinal lymph node assessment on PET/CT images without pixel-level annotations [0.03%]
无像素级标注的基于深度学习的PET/CT图像纵隔淋巴结评估方法研究
Sofija Engelson,Yannic Elser,Malte Maria Sieren et al.
Sofija Engelson et al.
Purpose: N -staging, a critical component in cancer diagnostics, quantifies metastatic involvement of lymph nodes and plays an important role in guiding treatment decisions. Manual assessment of lymph nodes on PET/CT sca...
MedPTQ: a practical pipeline for real post-training quantization in 3D medical image segmentation [0.03%]
MedPTQ：三维医学图像分割中实际部署的量化方法
Chongyu Qu,Ritchie Zhao,Ye Yu et al.
Chongyu Qu et al.
Purpose: Quantizing deep neural networks, reducing the precision (bit-width) of their computations, can remarkably decrease memory usage and accelerate processing, making these models more suitable for large-scale medical...
Conditional generative diffusion model for 3D trabecular bone synthesis with tunable microstructure [0.03%]
用于生成微结构可调的三维骨小梁的条件式生成扩散模型
Xin Wang,Gengxin Shi,Peiqin Teng et al.
Xin Wang et al.
Purpose: We aim to develop a conditional generative diffusion model capable of producing three-dimensional (3D) trabecular bone samples that can be tuned to achieve specific structural characteristics prescribed in terms ...
Utility of the virtual imaging trials methodology for objective characterization of AI systems and training data [0.03%]
虚拟影像试验方法在AI系统和训练数据客观表征中的效用
Fakrul Islam Tushar,Lavsen Dahal,Saman Sotoudeh-Paima et al.
Fakrul Islam Tushar et al.
Purpose: The credibility of artificial intelligence (AI) models for medical imaging continues to be a challenge, affected by the diversity of models, the data used to train the models, and the applicability of their combi...
How much of a face is a face: exploring reidentification potential with generative AI [0.03%]
人脸识别的限度：利用生成式AI探索重新识别潜力
Chloe Cho,Yihao Liu,Bohan Jiang et al.
Chloe Cho et al.
Purpose: Clinical photographs play an integral role across medical fields. Since the mid-20th century, deidentification has consisted of black bars covering specific facial features, typically the eyes alone. Although inc...
Importance of conditioning in latent diffusion models for image generation and super-resolution [0.03%]
潜在扩散模型在图像生成和超分辨率中的 Conditioning 作用的重要性
Dayvison Gomes de Oliveira,Franklin Anthony Ramos Coêlho,Thaís Gaudencio do Rêgo et al.
Dayvison Gomes de Oliveira et al.
Purpose: We investigate the use of latent diffusion models (LDMs) for synthesizing and enhancing photon-counting chest computed tomography (CT) images. We evaluate the models' capabilities in two main tasks: image generat...
Airway quantifications of bronchitis patients with photon-counting and energy-integrating computed tomography [0.03%]
基于单光子计数和能量积分CT的支气管炎患者的气道量化分析
Fong Chi Ho,William Paul Segars,Ehsan Samei et al.
Fong Chi Ho et al.
Purpose: Accurate airway measurement is critical for bronchitis quantification with computed tomography (CT), yet optimal protocols and the added value of photon-counting CT (PCCT) over energy-integrating CT (EICT) for re...
ER2Net: an evidential reasoning rule-enabled neural network for reliable triple-negative breast cancer tumor segmentation in magnetic resonance imaging [0.03%]
基于证据推理规则的神经网络在磁共振图像中可靠地分割三阴性乳腺癌肿瘤
Kazi Md Farhad Mahmud,Ahmad Qasem,Joshua M Staley et al.
Kazi Md Farhad Mahmud et al.
Purpose: Triple-negative breast cancer (TNBC) is an aggressive subtype with limited treatment options and high recurrence rates. Magnetic resonance imaging (MRI) is widely used for tumor assessment, but manual segmentatio...
From preoperative computed tomography to postmastoidectomy mesh construction: mastoidectomy shape prediction for cochlear implant surgery [0.03%]
从术前CT到术后乳突成形：人工耳蜗手术的乳突切除形状预测
Yike Zhang,Eduardo Davalos,Dingjie Su et al.
Yike Zhang et al.
Purpose: Cochlear implant (CI) surgery treats severe hearing loss by inserting an electrode array into the cochlea to stimulate the auditory nerve. An important step in this procedure is mastoidectomy, which removes part ...