Multistage Compression of Medical Images for Ultra Low Power Device Applications
D. Venugopal, Anita Raja · 2013
Nowadays a large number of various medical images are generated from hospitals and medical centers with sophisticated image acquisition devices. This paper deals about the techniques to decrease the communication bandwidth and to save the transmitting power in the wireless medical devices. Digital image consumes huge memory and thus digital image data compression is necessary in order to solve this problem. In medical applications such as disease diagnostic, the loss of information is unacceptable; hence medical images should be compressed lossless. Wireless medical devices injected into the body are battery operated devices and hence the lifetime of the battery should last for long time. Complexity of the compression algorithm is directly related to the power consumption of the processor and hence there is a need for simple compression algorithms. We proposed 2 simple algorithms which can be combined together or used separately based on the necessity to address this requirement. Medical imaging is a powerful and useful tool for radiologists and consultants, allowing them to improve and facilitate their diagnosis. Worldwide, X-ray images represents 60% of the total amount of radiological images, the remaining consists of more newly developed image modalities such as Computed Tomography(CT), Magnetic Resonance Imaging(MRI), Ultrasound(US), Positron Emission Tomography(PET), Nuclear Medicine(NM) and Digital Subtraction Angiography(DSA). Image communication systems for medical images have bandwidth and image size constraints that result in time consuming transmission of uncompressed raw image data. Thus image compression is a key factor to improve transmission speed and storage. It exploits common characteristics of most images that are the neighboring picture elements (pixels) are highly correlated. It means a typical still image contains a large amount of spatial redundancy in plain areas where adjacent pixels have almost the same values. Compression is the process of storing or packing data in a format that requires less space than the initial or original data. Compression techniques can be classified into lossy and lossless. Lossy compression permits some signal degradation and provide higher compression ratios in comparison with lossless techniques. This is used in applications dealing with speech and video signals where some loss of information can be tolerated.