The paper describes a computer tool dedicated to the comprehensive analysis of lung changes in computed tomography (CT) images. The correlation between the dose delivered during radiotherapy and pulmonary fibrosis is offered as an example analysis. The input data, in DICOM (Digital Imaging and Communications in Medicine) format, is provided from CT images and dose distribution models of patients. The CT images are processed using convolution neural networks, and next, the selected slices go through the segmentation and registration algorithms. The results of the analysis are visualized in graphical format and also in numerical parameters calculated based on the images analysis.

The paper presents a second order current mode sigma-delta modulator designed with the help of a new elaborated tool to optimize the transistor sizes. The circuit is composed of two continuous time loop filters, a current comparator and a one bit DAC with a current output. The resulting circuit, designed in a 65 nm 1.2 V CMOS technology, has a bandwidth of 2 MHz for a clock frequency of 250 MHz. The electrical simulation results show that it achieves a maximum signal-to-noise-plus-distortion ratio (SNDR) of 53.6 dB while dissipating 93 μW, which corresponds to an efficiency of 59.7 fJ/conv. The fully current mode structure makes the circuit suitable to be applied in a current mode signal processing like biosensors or image pixels arrays.

This paper presents an approach to a low-sensitivity design strategy for switched-current (SI) filter pairs based on a gyrator-capacitor prototype circuit. On the basis of a prototype filter, an SI counterpart circuit is obtained. Tools for SI filter design automation have been developed, which make a hardware description language - analog-mixed signal synthesization for the chosen kind of circuit. The obtained SI filter is better than the filter obtained using LC ladder structures with respect to very-large-scale integration complementary metal-oxide-semiconductor chip area and power consumption. Copyright © 2013 John Wiley & Sons, Ltd.

Radiation-induced lung injury remains a significant toxicity in thoracic radiotherapy. Because a precise diagnosis is difficult and commonly used assessment scales are unclear and subjective, there is a need to establish quantitative and sensitive grading methods. The lung tissue density change expressed in Hounsfield units (HUs) derived from CT scans seems a useful numeric surrogate. The study aimed to confirm a dose-response effect on HU value changes (ΔHU), their evolution in time, and the impact of selected clinical and demographic factors. We used dedicated, self-developed software to register and analyze 120 pairs of initial and follow-up CT scans of 47 lung cancer patients treated with dynamic arc radiotherapy. The differences in HU values between CT scans were calculated within discretized dose-bins limited by isodose lines. We have proved the dose-effect relationship, which is well described with a sigmoid model. We found the time evolution of HU changes to suit a typical clinical presentation of radiation-induced toxicity. Some clinical factors were found to correlate with ΔHU degree: planning target volume (PTV), V35 in the lung, patient’s age and a history of arterial hypertension, and initial lung ventilation intensity. Lung density change assessment turned out to be a sensitive and valuable method of grading post-RT lung toxicity.