Deep Learning for Accelerated Ultrasound Imaging

In portable, 3-D, or ultra-fast ultrasound (US) imaging systems, there is an increasing demand to reconstruct high quality images from limited number of data. However, the existing solutions require either hardware changes or computationally expansive algorithms. To overcome these limitations, here we propose a novel deep learning approach that interpolates the missing RF data by utilizing the sparsity of the RF data in the Fourier domain. Extensive experimental results from sub-sampled RF data from a real US system confirmed that the proposed method can effectively reduce the data rate without sacrificing the image quality.Comment: Invited paper for ICASSP 2018 Special Session for "Machine Learning in Medical Imaging: from Measurement to Diagnosis

Compact dual-band implantable antenna for e-health monitoring

Single Molecule Spectroscopy and Superresolution Imaging XI 2018 -- 27 January 2018 through 28 January 2018 -- 136394This work presents a compact dual-band Planar Inverted F-antenna (PIFA) antenna useful for E-health monitoring and wireless sensors systems. The antenna operates in the Industrial Standard and Medical (ISM) and Wireless Medical Telemetry Service (WMTS) bands. It offers a compact size with dimensions 12.6 × 8.5 × 2.4 mm3. Two different simulators have been used to verify the results. The proposed antenna performs well in the presence of a bio-compatible insulator (BCI) material

Peer review practices by medical imaging journals

ObjectiveTo investigate peer review practices by medical imaging journals.MethodsJournals in the category "radiology, nuclear medicine and medical imaging" of the 2018 Journal Citation Reports were included.ResultsOf 119 included journals, 62 (52.1%) used single-blinded peer review, 49 (41.2%) used double-blinded peer review, two (1.7%) used open peer review and one (0.8%) used both single-blinded and double-blinded peer reviews, while the peer review model of five journals (4.2%) remained unclear. The use of single-blinded peer review was significantly associated with a journal's impact factor (correlation coefficient of 0.218, P=0.022). On subgroup analysis, only subspecialty medical imaging journals had a significant association between the use of single-blinded peer review and a journal's impact factor (correlation coefficient of 0.354, P=0.025). Forty-eight journals (40.3%) had a reviewer preference option, 48 journals (40.3%) did not have a reviewer recommendation option, and 23 journals (19.3%) obliged authors to indicate reviewers on their manuscript submission systems. Sixty-four journals (53.8%) did not provide an explicit option on their manuscript submission Web site to indicate nonpreferred reviewers, whereas 55 (46.2%) did. There were no significant associations between the option or obligation to indicate preferred or nonpreferred reviewers and a journal's impact factor.ConclusionSingle-blinded peer review and the option or obligation to indicate preferred or nonpreferred reviewers are frequently employed by medical imaging journals. Single-blinded review is (weakly) associated with a higher impact factor, also for subspecialty journals. The option or obligation to indicate preferred or nonpreferred reviewers is evenly distributed among journals, regardless of impact factor

A bioinformatics potpourri

© 2018 The Author(s). The 16th International Conference on Bioinformatics (InCoB) was held at Tsinghua University, Shenzhen from September 20 to 22, 2017. The annual conference of the Asia-Pacific Bioinformatics Network featured six keynotes, two invited talks, a panel discussion on big data driven bioinformatics and precision medicine, and 66 oral presentations of accepted research articles or posters. Fifty-seven articles comprising a topic assortment of algorithms, biomolecular networks, cancer and disease informatics, drug-target interactions and drug efficacy, gene regulation and expression, imaging, immunoinformatics, metagenomics, next generation sequencing for genomics and transcriptomics, ontologies, post-translational modification, and structural bioinformatics are the subject of this editorial for the InCoB2017 supplement issues in BMC Genomics, BMC Bioinformatics, BMC Systems Biology and BMC Medical Genomics. New Delhi will be the location of InCoB2018, scheduled for September 26-28, 2018

The Bionic Radiologist: avoiding blurry pictures and providing greater insights

Radiology images and reports have long been digitalized. However, the potential of the more than 3.6 billion radiology examinations performed annually worldwide has largely gone unused in the effort to digitally transform health care. The Bionic Radiologist is a concept that combines humanity and digitalization for better health care integration of radiology. At a practical level, this concept will achieve critical goals: (1) testing decisions being made scientifically on the basis of disease probabilities and patient preferences; (2) image analysis done consistently at any time and at any site; and (3) treatment suggestions that are closely linked to imaging results and are seamlessly integrated with other information. The Bionic Radiologist will thus help avoiding missed care opportunities, will provide continuous learning in the work process, and will also allow more time for radiologists’ primary roles: interacting with patients and referring physicians. To achieve that potential, one has to cope with many implementation barriers at both the individual and institutional levels. These include: reluctance to delegate decision making, a possible decrease in image interpretation knowledge and the perception that patient safety and trust are at stake. To facilitate implementation of the Bionic Radiologist the following will be helpful: uncertainty quantifications for suggestions, shared decision making, changes in organizational culture and leadership style, maintained expertise through continuous learning systems for training, and role development of the involved experts. With the support of the Bionic Radiologist, disparities are reduced and the delivery of care is provided in a humane and personalized fashion

Sensor, Signal, and Imaging Informatics in 2017.

Objective To summarize significant contributions to sensor, signal, and imaging informatics literature published in 2017.Methods PubMed® and Web of Science® were searched to identify the scientific publications published in 2017 that addressed sensors, signals, and imaging in medical informatics. Fifteen papers were selected by consensus as candidate best papers. Each candidate article was reviewed by section editors and at least two other external reviewers. The final selection of the four best papers was conducted by the editorial board of the International Medical Informatics Association (IMIA) Yearbook.Results The selected papers of 2017 demonstrate the important scientific advances in management and analysis of sensor, signal, and imaging information.ConclusionThe growth of signal and imaging data and the increasing power of machine learning techniques have engendered new opportunities for research in medical informatics. This synopsis highlights cutting-edge contributions to the science of Sensor, Signal, and Imaging Informatics

AAPM medical physics practice guideline 10.a.: Scope of practice for clinical medical physics.

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education, and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline (MPPG) represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiation requires specific training, skills, and techniques as described in each document. As the review of the previous version of AAPM Professional Policy (PP)-17 (Scope of Practice) progressed, the writing group focused on one of the main goals: to have this document accepted by regulatory and accrediting bodies. After much discussion, it was decided that this goal would be better served through a MPPG. To further advance this goal, the text was updated to reflect the rationale and processes by which the activities in the scope of practice were identified and categorized. Lastly, the AAPM Professional Council believes that this document has benefitted from public comment which is part of the MPPG process but not the AAPM Professional Policy approval process. The following terms are used in the AAPM's MPPGs: Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances