AIMC Topic: Humans

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Seq2Morph: A deep learning deformable image registration algorithm for longitudinal imaging studies and adaptive radiotherapy.

Medical physics
PURPOSE: To simultaneously register all the longitudinal images acquired in a radiotherapy course for analyzing patients' anatomy changes for adaptive radiotherapy (ART).

Robot-patient registration for optical tracker-free robotic fracture reduction surgery.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Image-guided robotic surgery for fracture reduction is a medical procedure in which surgeons control a surgical robot to align the fractured bones by using a navigation system that shows the rotation and distance of bone mov...

Utilizing deep learning for dermal matrix quality assessment on in vivo line-field confocal optical coherence tomography images.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Line-field confocal optical coherence tomography (LC-OCT) is an imaging technique providing non-invasive "optical biopsies" with an isotropic spatial resolution of ∼1  μm and deep penetration until the dermis. Analysis of obtained images ...

Effect of Operative Time on Outcomes of Minimally Invasive Versus Open Pancreatoduodenectomy.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
OBJECTIVE: To evaluate how operative time interacts with outcomes among different approaches to pancreaticoduodenectomy (PD). Minimally invasive PDs (MIPD), which include laparoscopic (LPD) and robotic (RPD) approaches, are increasingly performed in ...

A systematic literature review for the prediction of anticancer drug response using various machine-learning and deep-learning techniques.

Chemical biology & drug design
Computational methods have gained prominence in healthcare research. The accessibility of healthcare data has greatly incited academicians and researchers to develop executions that help in prognosis of cancer drug response. Among various computation...

Electromyography-driven model-based estimation of ankle torque and stiffness during dynamic joint rotations in perturbed and unperturbed conditions.

Journal of biomechanics
The simultaneous modulation of joint torque and stiffness enables humans to perform large repertoires of movements, while versatilely adapting to external mechanical demands. Multi-muscle force control is key for joint torque and stiffness modulation...

Multi-stage classification of Alzheimer's disease from F-FDG-PET images using deep learning techniques.

Physical and engineering sciences in medicine
The study aims to implement a convolutional neural network framework that uses the 18F-FDG PET modality of brain imaging to detect multiple stages of dementia, including Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI)...

Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens.

Nature biomedical engineering
Multiplexed immunofluorescence imaging allows the multidimensional molecular profiling of cellular environments at subcellular resolution. However, identifying and characterizing disease-relevant microenvironments from these rich datasets is challeng...

Automated Detection of Cerebral Aneurysms on TOF-MRA Using a Deep Learning Approach: An External Validation Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Cerebral aneurysms yield the risk of rupture, severe disability and death. Thus, early detection of cerebral aneurysms is crucial to ensure timely treatment, if necessary. AI-based software tools are expected to enhance radiol...