More than 10 years experience with semiconductor pixel detectors for vertex detection in high energy physics experiments together with the steady progress in CMOS technology opened the way for the development of single photon processing pixel detectors for various applications including medical X-ray imaging. The state of the art of such pixel devices consists of pixel dimensions as small as 55x55 um2, electronic noise per pixel <100 e- rms, signal-to-noise discrimination levels around 1000 e- with a spread <50 e- and a dynamic range up to 32 bits per pixel. Moreover, the high granularity of hybrid pixel detectors makes it possible to probe inhomogeneities of the attached semiconductor sensor

Campbell, Michael

Heijne, Erik H M

Llopart-Cudie, Xavier

Mikulec, Bettina

Tlustos, Lukas

CERN Document Server

X-ray Imaging Using Single PhotonProcessing with Semiconductor PixelDetectorsB. Mikulec a,b,∗, M. Campbell a, E. Heijne a, X. Llopart a,L. Tlustos aaMedipix Collaboration, CERN, 1211 Geneva 23, Switzerlandbnow with the University of Geneva, 30 quai Ernest-Ansermet, 1211 Geneva 4,SwitzerlandAbstractMore than 10 years experience with semiconductor pixel detectors for vertex de-tection in high energy physics experiments together with the steady progress inCMOS technology opened the way for the development of single photon processingpixel detectors for various applications including medical X-ray imaging. The stateof the art of such pixel devices consists of pixel dimensions as small as 55 × 55µm2, electronic noise per pixel <100 e− rms, signal-to-noise discrimination levelsaround 1000 e− with a spread <50 e− and a dynamic range up to 32 bits per pixel.Moreover, the high granularity of hybrid pixel detectors makes it possible to probeinhomogeneities of the attached semiconductor sensor.Key words: single photon detection; quantum imaging; semiconductor detectors;X-ray imaging; Medipix1 IntroductionHybrid semiconductor detectors represent the basic tools to perform particletracking in the vertex region in high energy physics experiments. The intro-duction of silicon strip detectors into this field dates back to 1980 [1], whereassilicon pixel detectors appeared at the beginning of the 90’s [2]. Silicon sen-sors have considerably improved since then, but the continuing popularity of∗Email address: bettina.mikulec@cern.ch (B. Mikulec).Preprint submitted to Elsevier Science 10 May 2004CERN-OPEN-2006-05620/01/2003semiconductor detectors can be accredited mainly to progress in microelec-tronics. With reduced feature size the density of electronic components perunit area increases exponentially with time allowing increased functionalityper unit area and/or reduced pixel size. With deep sub-micron technology itis currently possible to squeeze about 200000 transistors into an area of 1mm2.Small pixel sizes and correspondingly tiny input capacitance together withhigh electronics component densities, optimized transistors and chip designopened the new field of quantum processing for imaging applications [3,4].Quantum processing implies that a particle signal can be distinguished frombackground noise. This noise discrimination is implemented with the help ofa noise reducing pre-amplifier shaper circuit and a discriminator in each read-out channel where it must be possible to set the discrimination level safelyabove the noise level. With steadily shrinking pixel sizes this concept gets morecomplicated as the signal charge from one particle might be shared betweena number of pixels. As a consequence, a solution should be found to sum upthe charge fractions belonging to the charge deposition of one particle andcompare the summed charge to a threshold [5].The simplest example of quantum processing is photon counting; as soon asthe processed signal passes the threshold the counter value of the readoutchannel is incremented. However there is a great potential to be explored withmore elaborated ways of processing single photon signals. Some projects startto use already two thresholds to select an energy band out of a continuousspectrum or perform subtraction images with one X-ray illumination (see ref-erences in [3]). For the future one can imagine to include a multi-bit ADC ineach readout cell to provide ’colour’ X-ray images [3,6]. Then it would alsobecome possible to weight each of the ADC channels with its ideal energyweighting factor to increase the image contrast [7]. Noise discrimination isabsolutely necessary to do low-dose or low-rate imaging, but it seems evidentby now that energy information is ultimately wanted as well.2 Detector requirements in medical imaging applicationsIn many aspects detector requirements for medical imaging applications arevery similar to high energy physics applications. These include the need forhigh true 2-dimensional spatial resolution and high sensitivity, but medicalimaging should deliver in addition the lowest possible dose to the patient.In general detector requirements depend strongly on the imaging task. There-fore detectors (sensors and electronics) should be optimized for different imag-ing applications. Protein crystallography, angiography, mammography or γ-ray imaging may have differing and sometimes conflicting requirements. Asmammography has some of the most stringent specifications within all medi-2cal imaging fields it was chosen as an example to illustrate the requirementsfor a dedicated imaging detector:(1) High spatial resolution: the required spatial resolution is different foranalog and digital systems. Analog systems must comply with a spa-tial resolution of 15-20 lp/mm 1 , whereas 5-13 lp/mm for digital systemsseem to be equivalent (see next point). High spatial resolution is neces-sary to detect tiny micro-calcifications, early indicators of breast cancer.This point is addressed in hybrid semiconductor detector developmenton one hand through steadily evolving miniaturization and on the otherhand through direct detection of the X-rays in the semiconductor sensorwithout conversion layer (as used with CCD’s, film and most flat panelimagers) to avoid image blurring.(2) High contrast resolution <3%: Contrast resolution is the greatest advan-tage of digital imaging systems compared to analog ones. Especially inregions of low detector illumination film is limited by the so-called foglevel in the toe region of its characteristic curve. Superior contrast resolu-tion is expected to be most beneficial for cancer detection in radiodensebreasts (e.g. for younger women). Quantum processing can improve con-trast resolution considerably.(3) Uniform response: related to the previous point; for hybrid detectors thispoint concerns in particular the sensors (see section 4).(4) Patient dose <3mGy: To achieve low patient dose without informationloss it is necessary to have imaging systems with high DQE 2 over awide spatial frequency range. This implies high absorption and chargecollection efficiency of the sensor as well as good noise performance of thereadout chain. Direct detection and quantum processing are beneficial aswell [7–9]. It is evident that the system has to possess as well sufficientcounting rate capability.(5) Image area 18× 24 (24× 30) cm2: This is still an unsolved problem for hy-brid pixel detectors. One solution adopted especially with strip detectorsis a scanning slit system with a linear detector covering one dimension.Pixel chips can now be designed to be 3-side buttable which enables tomake continuous arrays of pixel detectors along 3 sides. The forth sideis still needed for I/O. To solve this problem it might be possible in thefuture to make use of a technique increasingly popular in microelectronicsindustry, which is to etch holes through the readout chip to route powersupply and other signal lines.(6) Digital system(7) Compactness, simple handling, stable operation, no cooling...(8) Cheap1 lp/mm...line pairs per mm2 DQE...detective quantum efficiency33 The Medipix single photon processing ASICsThe Medipix1 chip was the first full-size photon counting ASIC and was de-signed with mainly mammography and dental imaging in view [10]. It emergedfrom experience gained with the design and the application of pixel chips forhigh energy physics experiments; parts of the front-end of the Medipix1 chipwere even taken over from the Omega3/LHC1 pixel chip. The Medipix1 chiphas been extensively studied over the years leading to the design of an im-proved version of the chip, Medipix2, within the framework of the Medipix2collaboration [5,11]. Just recently, Medipix2 arrived back from the foundry aswell as the first Medipix2/Si assemblies. First electrical measurement resultsshow that the chip is working in agreement with the simulations [12]. Table 1shows a comparison between Medipix1 and Medipix2.Medipix1 Medipix2square pixels; 170 µm at the side square pixels; 55 µm at the side64 × 64 pixels (4096) 256 × 256 pixels (65536)sensitive to pos. input charge sensitive to pos. and neg. input charge;free choice of sensor materialsensor leakage current compensation pixel-by-pixel sensor leakage currentcolumnwise compensationone discriminator two discriminators (energy window)designed to be linear over a wide range15-bit counter per pixel 13-bit counter per pixelmax. counting rate ≈1 MHz/pixel max. counting rate ≈1 MHz/pixel(3.5 GHz/cm2) (33 GHz/cm2)3 × 3 matrix of pixels with analogoutput to study charge sharing3-side buttableparallel I/O serial or parallel I/O1 µm SACMOS technology 0.25 µm technology(1.6M transistors/chip) (33M transistors/chip)Table 1Comparison between the Medipix1 and the Medipix2 single photon processing pixelchips.4In fig. 1 (left) an image of a 300 µm thick copper mask was taken with a 109Cdsource and one of the first bump-bonded Medipix2/Si assemblies to give animpression of the tiny pixel size. The chip used for this image came fromthe first production run which showed a yield problem resulting in some deadcolumns. Moreover, during bump-bonding the sensor was shifted by three rowswith respect to the chip. This misalignment is visible as 3 dead rows at thebottom of the image and means that the guardring of the sensor was not con-nected. Neglecting these problems, the resulting image is very promising.As a comparison an image of the same object under similar measurement con-ditions was made with a Medipix1/Si assembly (see right fig. 1) 3 . Due to thelarger pixel size the number of counts/pixel is higher, but the contour of theletters is much worse.0501001502002500 50 100 150 200 25002040608010012001020304050600 10 20 30 40 50 600200400600800100012001400Fig. 1. Image of a copper mask taken with a 109Cd source; the left image comesfrom a Medipix2/Si assembly, the right one from a Medipix1/Si assembly.At present, Medipix2 is the single photon processing pixel chip with the small-est pixel size and the highest counting rate per unit area. It will offer the possi-bility to study optimal pixel sizes for different applications and the implicationof charge sharing effects to DQE and contrast resolution.4 Low and high frequency noise in silicon detectorsFor medical imaging applications it is imperative to reach a high DQE as men-tioned before. The DQE describes how the SNR at the input of the imagingsystem (SNRin) is transferred to the output (SNRout) and can be written as3 The top right corner of the assembly shows some bump-bonding problems.5SNR2out/SNR2in. Taking uniform illuminations of several Medipix1/Si assem-blies (flood images) it was seen that the SNR defined in this case simply bythe fraction (mean number of counts/sigma of the count distribution) quicklyflattens out at values around 20 instead of following a square root dependencepredicted by Poisson statistics. Nevertheless, applying a flat field correctionresulted in a curve representing the theoretically predicted limit over the fulldynamic range of the chip and reaching values of SNR>160 [3]. The flat fieldcorrection is a correction method applied routinely in the imaging field. Itconsists of multiplying each imaging element with its calibration or ’efficiency’factor attributed beforehand with a certain number of flood fields. Investiga-tion were therefore started to understand the reasons for the relatively largespread in counts under uniform illumination without flat field correction.Several observations were made and are summarized below [3,13,14]:(a) Low spatial frequency patterns: The silicon detectors show a ’wave’ pat-tern of higher and lower counting regions, in particular visible while work-ing in under-depletion. These ’waves’ of period of the order of 1 mm moveslightly increasing the detector bias voltage from a few volts until the de-pletion voltage (≈20 V in our case). Increasing the bias voltage further,the location of the waves is stable and the amplitude decreases. Neverthe-less, even at voltages above 100 V the wave structure is still visible withcount variations around ±2%. This low frequency noise has been ascribedto bulk inhomogeneities due to doping fluctuations during crystal growth(see [15]). As it is stable in time it can be corrected for with a flat fieldcorrection made at the corresponding detectors bias voltage.(b) High spatial frequency pattern: Besides the macroscopic fluctuations men-tioned in (a) a fixed pattern noise locally varying from pixel to pixel hasbeen observed. This high frequency noise is independent in its locationfrom the applied bias. A flat field map made even in under-depletioncan smoothen the pixel-to-pixel variations of an image taken in over-depletion. The reason for this observed high frequency noise is still underinvestigation. Possible explanations might be variations in the pixel ge-ometry and/or electric field components parallel to the pixel surface dueto doping inhomogeneities, which lead to differences in charge collection,or threshold variations.(c) Energy dependence of the flat field correction: It has been observed thatthe flat field correction was ineffective in the case of an image taken with amammographic phantom (objects embedded in 4 cm thick PMMA) and aMo X-ray tube (spectral X-ray source) where the flat field was calculatedin the absence of any PMMA. Due to the higher absorption probabilityof low energy X-rays in the PMMA (or the patient) compared to X-raysfrom the upper end of the spectrum, the X-ray spectrum incident on thedetector is hardened. This results in a different mean conversion depthof the X-rays in the sensor leading to a different count distribution onthe pixel matrix. Under real medical imaging conditions this represents6a problem as it might result in image artifacts and false diagnosis. Fortu-nately it was shown that an interpolated flat field map could effectivelycorrect the data [14]. Thus, provided the thickness and density of theimaged object is known an appropriate flat field correction can be used.To conclude, it has been shown that single photon pixel detectors with smallpixel size can be used as well to probe the connected semiconductor sensor.Even silicon sensors show pronounced low and high spatial frequency patternsin the count distribution of a uniform illumination. Due to the energy depen-dence of some correction methods used for imaging applications it would bedesirable to improve the sensor uniformity.5 ConclusionsSingle photon processing is becoming more and more popular for various kindsof imaging applications due to its advantages compared to charge integratingsystems. 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X-ray imaging using single photon processing with semiconductor pixel detectors

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