Cloud computing is rapidly emerging as a preferred solution for the challenges of Big Data, mobility and access to information on demand, any time, from anywhere.  Although a late arrival to the scene, healthcare has been making up for lost time in terms of embracing the Cloud.

Healthcare and Big Data
In reality, there is little choice. Healthcare is among the largest contributors to Big Data, not least because of the explosion in massive graphic files which constitute Picture Archiving and Communication Systems (PACS). Coping with exabytes of information, growing by the second, has made traditional physical storage a relic. Data storage has become virtual, with the computing process moving to the data rather than the other way round.
In the healthcare context, this is pertinent given that physician interaction with PACS and other clinical information systems is what gives the data meaning. With 75% of physicians using a smartphone and more than 10,000 mobile health applications already in use, healthcare carries some of the biggest and most exacting requirements for mobility, scalability and security.
The above scenarios are central to the Cloud computing offer, and they have guided its development and refinement from the outset.

The Cloud: enhancing healthcare quality and cost-effectiveness
Cloud computing technologies can assist healthcare providers

During the last decade the field of medical imaging has advanced by leaps and bounds facilitated by innovations in ultrasound, MRI, CT and PET technologies as well as dual modality approaches such as PET/MRI and PET/CT. These developments have allowed faster scanning and acquisition of clearer, coloured 3D images, whilst automatic dose regulation for imaging technologies involving ionizing radiation is inexorably lowering the dose to which patients are exposed. Use of ultrasound has expanded well beyond obstetrics, MRI is now routine in neurology, high speed CT imaging is the standard practice in cardiology and PET has become integral to modern oncology.
Both hospitals and patients have clearly benefited from all these innovations, with studies correlating use of relevant imaging modalities in accident and emergency departments with shorter patient waiting times and fewer hospital admissions. In the case of inpatients, use of medical imaging has been correlated with shorter hospital stays, a reduced need for exploratory surgery and a decline in mortality. Sadly, though, as financial problems continue to affect much of Europe as well as the US and Japan, the increasing costs incurred for medical imaging technology are becoming economically unsustainable. Is it possible to reduce these costs yet continue to deliver quality healthcare?
The purchase of refurbished rather than new equipment is increasingly becoming a prudent way for hospitals and clinics to reduce costs in the developed as well as less developed countries. Because technological advances have been so swift, larger (and wealthier) institutions may replace their quality MRI or CT systems with even more up to date models and

Image-guided surgery (IGS) involves correlating pre-surgical images of an operative area and its adjacent anatomic structures to a surgical instrument, and achieving this with a high degree of precision, in real time.
IGS, in some senses, can be considered as an enhancement of minimally invasive surgery (MIS), which became widespread during the 1980s and early 1990s. Like IGS, MIS too had the goal of providing precise access and reducing collateral damage to nearby tissue during a surgical procedure.

IGS and Computer Assisted Surgery
IGS is now seen as a key component of computer assisted surgery (CAS), a methodology to use computers in the surgical process, all the way from pre-operative planning to intervention and post-surgery assessments. The two terms were often used interchangeably in the past, and still overlap in several features and applications, such as the use of virtual or augmented reality.
However, given the emergence in its own right of another specialty application, robotic surgery, CAS is now differentiating itself from IGS.

Graphic processor capabilities drive IGS
Both CAS and IGS were driven by the explosive growth of computing power in the late 1990s and the consequent availability of structured patient information in the operating theatre.
IGS, however, has a more targeted heritage in the field of graphic processor units (GPUs). Aided by advanced algorithms in areas such as dynamic texture binding, texture sampling, rendering and image compositing, these have enabled