The effects of gray scale image processing on digital mammography interpretation performance

RATIONALE AND OBJECTIVES: To determine the effects of three image-processing algorithms on diagnostic accuracy of digital mammography in comparison with conventional screen-film mammography. MATERIALS AND METHODS: A total of 201 cases consisting of nonprocessed soft copy versions of the digital mammograms acquired from GE, Fischer, and Trex digital mammography systems (1997-1999) and conventional screen-film mammograms of the same patients were interpreted by nine radiologists. The raw digital data were processed with each of three different image-processing algorithms creating three presentations-manufacturer's default (applied and laser printed to film by each of the manufacturers), MUSICA, and PLAHE-were presented in soft copy display. There were three radiologists per presentation. RESULTS: Area under the receiver operating characteristic curve for GE digital mass cases was worse than screen-film for all digital presentations. The area under the receiver operating characteristic for Trex digital mass cases was better, but only with images processed with the manufacturer's default algorithm. Sensitivity for GE digital mass cases was worse than screen film for all digital presentations. Specificity for Fischer digital calcifications cases was worse than screen film for images processed in default and PLAHE algorithms. Specificity for Trex digital calcifications cases was worse than screen film for images processed with MUSICA. CONCLUSION: Specific image-processing algorithms may be necessary for optimal presentation for interpretation based on machine and lesion type.     

Image processing algorithms for digital mammography: a pictorial essay.

Digital mammography systems allow manipulation of fine differences in image contrast by means of image processing algorithms. Different display algorithms have advantages and disadvantages for the specific tasks required in breast imaging-diagnosis and screening. Manual intensity windowing can produce digital mammograms very similar to standard screen-film mammograms but is limited by its operator dependence. Histogram-based intensity windowing improves the conspicuity of the lesion edge, but there is loss of detail outside the dense parts of the image. Mixture-model intensity windowing enhances the visibility of lesion borders against the fatty background, but the mixed parenchymal densities abutting the lesion may be lost. Contrast-limited adaptive histogram equalization can also provide subtle edge information but might degrade performance in the screening setting by enhancing the visibility of nuisance information. Unsharp masking enhances the sharpness of the borders of mass lesions, but this algorithm may make even an indistinct mass appear more circumscribed. Peripheral equalization displays lesion details well and preserves the peripheral information in the surrounding breast, but there may be flattening of image contrast in the nonperipheral portions of the image. Trex processing allows visualization of both lesion detail and breast edge information but reduces image contrast.     

Improving the Detection of Simulated Masses in Mammograms through Two Different Image-Processing Techniques

RATIONALE AND OBJECTIVES: The purpose of this study was to determine whether contrast-limited adaptive histogram equalization (CLAHE) or histogram-based intensity windowing (HIW) improves the detection of simulated masses in dense mammograms. MATERIALS AND METHODS: Simulated masses were embedded in portions of mammograms of patients with dense breasts; the mammograms were digitized at 50 microm per pixel, 12 bits deep. In two different experiments, images were printed both with no processing applied and with related parameter settings of two image-processing methods. A simulated mass was embedded in a realistic background of dense breast tissue, with its position varied. The key variables in each trial included the position of the mass, the contrast levels of the mass relative to the background, and the selected parameter settings for the image-processing method. RESULTS: The success in detecting simulated masses on mammograms with dense backgrounds depended on the parameter settings of the algorithms used. The best HIW setting performed better than the best fixed-intensity window setting and better than no processing. Performance with the best CLAHE settings was no different from that with no processing. In the HIW experiment, there were no significant differences in observer performance between processing conditions for radiologists and nonradiologists. CONCLUSION: HIW should be tested in clinical images to determine whether the detection of masses by radiologists can be improved. CLAHE processing will probably not improve the detection of masses on clinical mammograms.     

Digital mammography. ROC studies of the effects of pixel size and unsharp-mask filtering on the detection of subtle microcalcifications

We investigated the spatial resolution requirement and the effect of unsharp-mask filtering on the detectability of subtle microcalcifications in digital mammography. Digital images were obtained by digitizing conventional screen-film mammograms with a 0.1 X 0.1 mm2 pixel size, processed with unsharp masking, and then reconstituted on film with a Fuji image processing/simulation system (Fuji Photo Film Co., Tokyo, Japan). Twenty normal cases and 12 cases with subtle microcalcifications were included. Observer performance experiments were conducted to assess the detectability of subtle microcalcifications in the conventional, the unprocessed digital, and the unsharp-masked mammograms. The observer response data were evaluated using receiver operating characteristic (ROC) and LROC (ROC with localization) analyses. Our results indicate that digital mammograms obtained with 0.1 X 0.1 mm2 pixels provide lower detectability than the conventional screen-film mammograms. The detectability of microcalcifications in the digital mammograms is improved by unsharp-mask filtering; the processed mammograms still provide lower accuracy than the conventional mammograms, however, chiefly because of increased false-positive detection rates for the processed images at each subjective confidence level. Viewing unprocessed digital and unsharp-masked images in pairs resulted in approximately the same detectability as that obtained with the unsharp-masked images alone. However, this result may be influenced by the fact that the same limited viewing time was necessarily divided between the two images.     

Comparing the performance of mammographic enhancement algorithms: a preference study

OBJECTIVE: The objective of this study was to compare the performance of four image enhancement algorithms on secondarily digitized (i.e., digitized from film) mammograms containing masses and microcalcifications of known pathology in a clinical soft-copy display setting. MATERIALS AND METHODS: Four different image processing algorithms (adaptive unsharp masking, contrast-limited adaptive histogram equalization, adaptive neighborhood contrast enhancement, and wavelet-based enhancement) were applied to one image of secondarily digitized mammograms of forty cases (10 each of benign and malignant masses and 10 each of benign and malignant microcalcifications). The four enhanced images and the one unenhanced image were displayed randomly across three high-resolution monitors. Four expert mammographers ranked the unenhanced and the four enhanced images from 1 (best) to 5 (worst). RESULTS: For microcalcifications, the adaptive neighborhood contrast enhancement algorithm was the most preferred in 49% of the interpretations, the wavelet-based enhancement in 28%, and the unenhanced image in 13%. For masses, the unenhanced image was the most preferred in 58% of cases, followed by the unsharp masking algorithm (28%). CONCLUSION: Appropriate image enhancement improves the visibility of microcalcifications. Among the different algorithms, the adaptive neighborhood contrast enhancement algorithm was preferred most often. For masses, no significant improvement was observed with any of these image processing approaches compared with the unenhanced image. Different image processing approaches may need to be used, depending on the type of lesion. This study has implications for the practice of digital mammography.     

Gastrointestinal examinations with digital radiography.

Basic imaging properties and clinical usefulness of an upgraded digital radiography system were evaluated. The system, which has 1,024 x 1,024 and 2,048 x 2,048 matrices, was upgraded with smaller focal spots (0.3 and 0.8 mm) and reduced thickness of the photoconductive layer of the video camera. Screen-film and digital images (with and without postprocessing) of the upper and lower gastrointestinal (GI) tract were used in the clinical evaluation. Overall modulation transfer functions of the upgraded digital system were comparable to those of the screen-film system, especially at the lower spatial frequency. Threshold contrasts of the two systems were similar despite a 50% reduction in incident exposure for the digital system. For the upper GI tract, digital images processed with unsharp masking techniques were comparable in quality to screen-film images before and after upgrade of the system. For the lower GI tract, screen-film images were better than digital images, except for those produced with a 2,048 x 2,048 matrix with unsharp masking. Further evaluation of the system for examination of other parts of the body seems warranted.     

Mammographic characteristics of 115 missed cancers later detected with screening mammography and the potential utility of computer-aided detection

PURPOSE: To retrospectively determine the mammographic characteristics of cancers missed at screening mammography and assess the ability of computer-aided detection (CAD) to mark the missed cancers. MATERIALS AND METHODS: A multicenter retrospective study accrued 1,083 consecutive cases of breast cancer detected at screening mammography. Prior mammograms were available in 427 cases. Of these, 286 had lesions visible in retrospect. The 286 cases underwent blinded review by panels of radiologists; a majority recommended recall for 112 cases. Two experienced radiologists compared prior mammograms in 110 of these cases with the subsequent screening mammograms (when cancer was detected), noting mammographic characteristics of breast density, lesion type, size, morphology, and subjective reasons for possible miss. The prior mammograms were then analyzed with a CAD program. RESULTS: There were 110 patients with 115 cancers. On the prior mammograms with missed cancers, 35 (30%) of the 115 lesions were calcifications, with 17 of 35 (49%) clustered or pleomorphic. Eighty of the 115 (70%) were mass lesions, with 32 of 80 (40%) spiculated or irregular. For calcifications and masses, the most frequently suggested reasons for possible miss were dense breasts (12 of 35; 34%) and distracting lesions (35 of 80; 44%), respectively. CAD marked 30 (86%) of 35 missed calcifications and 58 (73%) of 80 missed masses. CONCLUSION: Detection errors affected cases with calcifications and masses. CAD marked most (77%; 88 of 115) cancers missed at screening mammography that radiologists retrospectively judged to merit recall.     

Investigation of reduction of exposure dose in digital mammography: relationship between exposure dose and image processing

In digital mammograms, granularity is an important image property for the detection of microcalcifications and masses. Therefore, we investigated the relationship between the conditions of various exposure doses and the detectability of RMI156 phantom images with and without image processing for the reduction of exposure dose. The images are processed with Gaussian filter and unsharp-masking filters to evaluate the effects on image properties by using the digital Wiener spectrum (WS) presampled modulation transfer function (MTF). In addition, observer performance tests for the detectability of microcalcifications and masses are performed. With Gaussian filtering, the WS value decreased to 50% at 2.0 cycles/mm and the detectability score of masses increased 80% and 12%, on 1.34 mGy and 2.62 mGy, respectively (p<0.05). With unsharp-masking (7 x 7 pixels), the MTF value increased to 126% at 2.0 cycles/mm, and the detectability of microcalcification to 32% and 5%, on 1.34 mGy and 5.28 mGy, respectively (p<0.05) compared with the original image. The optimal dose of simulated lesions with unsharp masking became 5.25 mGy. The unsharp masking could reduce 37% of the exposure dose without a loss of detectability of microcalcifications and masses.     

Detection of simulated microcalcifications in fixed mammary tissue: An ROC study of the effect of local versus global histogram equalization

PURPOSE: To investigate whether sliding window adaptive histogram equalization (SWAHE) of digital mammograms improves the detection of simulated calcifications, as compared to images normalized by global histogram equalization (GHE). MATERIAL AND METHODS: Direct digital mammograms were obtained from mammary tissue phantoms superimposed with different frames. Each frame was divided into forty squares by a wire mesh, and contained granular calcifications randomly positioned in about 50% of the squares. Three radiologists read the mammograms on a display monitor. They classified their confidence in the presence of microcalcifications in each square on a scale of 1 to 5. Images processed with GHE were first read and used as a reference. In a later session, the same images processed with SWAHE were read. RESULTS: The results were compared using ROC methodology. When the total areas AZ were compared, the results were completely equivocal. When comparing the high-specificity partial ROC area AZ,0.2 below false-positive fraction (FPF) 0.20, two of the three observers performed best with the images processed with SWAHE. The difference was not statistically significant. CONCLUSION: When the reader's confidence threshold in malignancy is set at a high level, increasing the contrast of mammograms with SWAHE may enhance the visibility of microcalcifications without adversely affecting the false-positive rate. When the reader's confidence threshold is set at a low level, the effect of SWAHE is an increase of false positives. Further investigation is needed to confirm the validity of the conclusions.     

Breast cancer risk prediction model: a nomogram based on common mammographic screening findings

Objectives

To develop a prediction model for breast cancer based on common mammographic findings on screening mammograms aiming to reduce reader variability in assigning BI-RADS.

Methods

We retrospectively reviewed 352 positive screening mammograms of women participating in the Dutch screening programme (Nijmegen region, 2006–2008). The following mammographic findings were assessed by consensus reading of three expert radiologists: masses and mass density, calcifications, architectural distortion, focal asymmetry and mammographic density, and BI-RADS. Data on age, diagnostic workup and final diagnosis were collected from patient records. Multivariate logistic regression analyses were used to build a breast cancer prediction model, presented as a nomogram.

Results

Breast cancer was diagnosed in 108 cases (31 %). The highest positive predictive value (PPV) was found for spiculated masses (96 %) and the lowest for well-defined masses (10 %). Characteristics included in the nomogram are age, mass, calcifications, architectural distortion and focal asymmetry.

Conclusion

With our nomogram we developed a tool assisting screening radiologists in determining the chance of malignancy based on mammographic findings. We propose cutoff values for assigning BI-RADS in the Dutch programme based on our nomogram, which will need to be validated in future research. These values can easily be adapted for use in other screening programmes.

Key points

? There is substantial reader variability in assigning BI-RADS in mammographic screening. ? There are no strict guidelines linking mammographic findings to BI-RADS categories. ? We developed a model (nomogram) predicting the presence of breast cancer. ? Our nomogram is based on common findings on positive screening mammograms. ? The nomogram aims to assist screening radiologists in assigning BI-RADS categories.     

Independent evaluation of computer classification of malignant and benign calcifications in full-field digital mammograms

RATIONALE AND OBJECTIVES: To evaluate whether a computer-aided diagnosis (CADx) technique can accurately classify breast calcifications in full-field digital mammograms (FFDMs) as malignant or benign. The computer technique was developed previously on screen-film mammograms (SFMs) in which individual calcifications were identified manually. The present study evaluated the computer technique independently on a new database of FFDM images with automatic detection of the individual calcifications. MATERIALS AND METHODS: We analyzed 49 consecutive FFDM cases (19 cancers) that showed suspicious calcifications. Four mammography radiologists read soft-copy mammograms retrospectively and electronically indicated the region of calcifications in each image. The computer then automatically detected the individual calcifications within the indicated region and analyzed eight features of calcification morphology and distribution to arrive at an estimated likelihood of malignancy. The radiologists entered Breast Imaging Report and Data System assessments before and after seeing the computer results. Performance was analyzed using receiver operating characteristic analysis. RESULTS: Despite variability in radiologist-indicated regions of calcifications, the computer achieved consistently high performance taking input from the four radiologists (receiver operating characteristic curve area, A(z): 0.80, 0.80, 0.78, and 0.77; differences not statistically significant). Previous results showed that the computer technique achieved an A(z) value of 0.80 on SFMs, which improved radiologists' performance significantly. CONCLUSIONS: The computer technique appears to maintain consistently high performance in classifying calcifications in FFDMs as malignant or benign without requiring substantial modification from its initial development on SFMs. The computer performance appears to be robust with respect to variations in radiologists' input.     

Diagnostic accuracy of digital mammography in patients with dense breasts who underwent problem-solving mammography: effects of image processing and lesion type

PURPOSE: To determine effects of lesion type (calcification vs mass) and image processing on radiologist's performance for area under the receiver operating characteristic curve (AUC), sensitivity, and specificity for detection of masses and calcifications with digital mammography in women with mammographically dense breasts. MATERIALS AND METHODS: This study included 201 women who underwent digital mammography at seven U.S. and Canadian medical centers. Three image-processing algorithms were applied to the digital images, which were acquired with Fischer, General Electric, and Lorad digital mammography units. Eighteen readers participated in the reader study (six readers per algorithm). Baseline values for reader performance with screen-film mammograms were obtained through the additional interpretation of 179 screen-film mammograms. A repeated-measures analysis of covariance allowing unequal slopes was used in each of the nine analyses (AUC, sensitivity, and specificity for each of three machines). Bonferroni correction was used. RESULTS: Although lesion type did not affect the AUC or sensitivity for Fischer digital images, it did affect specificity (P =.0004). For the General Electric digital images, AUC, sensitivity, and specificity were not affected by lesion type. For Lorad digital images, the results strongly suggested that lesion type affected AUC and sensitivity (P <.0001). None of the three image-processing methods tested affected the AUC, sensitivity, or specificity for the Fischer, General Electric, or Lorad digital images. CONCLUSION: Findings in this study indicate that radiologist's interpretation accuracy in interpreting digital mammograms depends on lesion type. Interpretation accuracy was not influenced by the image-processing method.     

Computer-aided diagnosis of masses with full-field digital mammography

RATIONALE AND OBJECTIVES: The authors developed and evaluated a method of computer-aided diagnosis (CAD) for mass detection with full-field digital mammography (FFDM). MATERIALS AND METHODS: The new CAD method for FFDM employs adaptive, nonlinear multiscale processing and hybrid classification methods. The major strategies are (a) to "standardize" the mammographic image before it is input to the analysis modules, (b) to adapt the segmentation of suspicious regions adapt to accommodate different characteristics of masses and mammograms, and (c) to use combined "hard" and "soft" decision making in discriminating between mass and normal tissue regions. Two data sets of diagnostic FFDM mammograms were used. The training data set includes 36 normal and 24 abnormal mammograms (34 masses), and the testing data set includes 24 normal and 10 abnormal mammograms (10 masses). The tumors in this diagnostic database were more subtle and difficult to detect than those in screening databases the authors have used before. RESULTS: With the limited database and a partial optimization, a sensitivity of 91% was obtained in training, with a false-positive rate of 3.21 per image. At this trained operating point of the CAD system, six of 10 subtle masses were detected in testing. CONCLUSION: The CAD algorithms developed in screen-film mammography can be modified for FFDM. More data analysis and system optimization and evaluation will be needed before CAD can be integrated efficiently into the performance of FFDM.     

Mammographic microcalcifications: detection with xerography, screen- film, and digitized film display

Pulverized bone specks and aluminum oxide specks were measured by hand into sizes ranging from 0.2 mm to 1.0 mm and then arranged in clusters. These clusters were superimposed on a human breast tissue phantom, and xeromammograms and screen-film mammograms of the clusters were made. The screen-film mammograms were digitized using a high-resolution laser scanner and then displayed on cathode ray tube (CRT) monitors. Six radiologists independently counted the microcalcifications on the xeromammograms, the screen-film mammograms, and the digitized-film mammograms. The xeromammograms were examined with a magnifying glass; the screen-film images were examined with a magnifying glass and by hot light; and the digitized-film images were examined by electronic magnification and image processing. The bone speck size that corresponded to a mean 50% detectability level for each technique was as follows: xeromammography, 0.550 mm; digitized film, 0.573 mm; and screen-film, 0.661 mm. We postulate that electronic magnification and image processing with edge enhancement can improve the capability of screen-film mammography to enhance the detection of microcalcifications.     

Screen film vs full-field digital mammography: image quality,detectability and characterization of lesions

The objective of this study was to compare screen-film mammography (SFM) to full-field digital mammography (FFDM) regarding image quality as well as detectability and characterization of lesions using equivalent images of the same patient acquired with both systems. Two mammography units were used, one with a screen-film system (Senographe DMR) and the other with a digital detector (Senographe 2000D, both GEMS). Screen-film and digital mammograms were performed on 55 patients with cytologically or histologically proven tumors on the same day. Together with these, 75 digital mammograms of patients without tumor and the corresponding previous screen-film mammograms not older than 1.5 years were reviewed by three observers in a random order. Contrast, exposure, and the presence of artifacts were evaluated. Different details, such as the skin, the retromamillary region, and the parenchymal structures, were judged according to a three-point ranking scale. Finally, the detectability of microcalcifications and lesions were compared and correlated to histology. Image contrast was judged to be good in 76%, satisfactory in 20%, and unsatisfactory in 4% of screen-film mammograms. Digital mammograms were judged to be good in 99% and unsatisfactory in 1% of cases. Improper exposure of screen-film system occurred in 18% (10% overexposed and 8% underexposed). Digital mammograms were improperly exposed in 4% of all cases but were of acceptable quality after post-processing. Artifacts, most of them of no significance, were found in 78% of screen-film and in none of the digital mammograms. Different anatomical regions, such as the skin, the retromamillary region, and dense parenchymal areas, were better visualized in digital than in screen-film mammography. All malignant tumors were seen by the three radiologists; however, digital mammograms allowed a better characterization of these lesions to the Breast Imaging Reporting and Data System (BI-RADS;) [corrected] categories (FFDM better than SFM in 23 of 165 vs 9 of 165 judged cases in SFM). In conclusion, digital mammography offers a consistent, high image quality in combination with a better contrast and without artifacts. Lesion detection in digital images was equal to that in screen-film images; however, categorization of the lesions to the BI-RADS classification was slightly better.     

Digital mammography: what do we and what don’t we know?

High-quality full-field digital mammography has been available now for several years and is increasingly used for both diagnostic and screening mammography. A number of different detector technologies exist, which all have their specific advantages and disadvantages. Diagnostic accuracy of digital mammography has been shown to be at least equivalent to film-screen mammography in a general screening population. Digital mammography is superior to screen-film mammography in younger women with dense breasts due to its ability to selectively optimize contrast in areas of dense parenchyma. This advantage is especially important in women with a genetic predisposition for breast cancer, where intensified early detection programs may have to start from 25 to 30 years of age. Tailored image processing and computer-aided diagnosis hold the potential to further improve the early detection of breast cancer. However, at present no consensus exists among radiologists on which processing is optimal for digital mammograms. Image processing may also vary significantly among vendors with so far limited interoperability. This review aims to summarize the available information regarding the impact of digital mammography on workflow and breast cancer diagnosis.     

Value of increasing film processing time to reduce radiation dose during mammography

We systematically tested the effects on radiation dose and image quality of increasing the mammographic film processing time from the standard 90 sec to 3 min. Hurter and Driffield curves were obtained for a Kodak Min-R-OM1-SO177 screen-film combination processed with Kodak chemistry. Image contrast and radiation dose were measured for two tissue-equivalent breast phantoms. We also compared sequential pairs of mammograms, one processed at 90 sec and one at 3 min, from 44 patients on the basis of nine categories of image quality. Increased processing time reduced breast radiation dose by 30%, increased contrast by 11%, and produced slight overall gains in image quality. Simple modifications can convert a 90-sec processor to a 3-min unit. We recommend that implementation of extended processing be considered, especially by those centers that obtain a large number of screening mammograms. Three-minute film processing can reduce breast radiation dose by 30% and increase contrast by 11% without compromising image quality.     

Image quality of digital mammography images produced using wet and dry laser imaging systems

IntroductionA study was carried out to compare the quality of digital mammographic images printed or processed by a wet laser imaging system and a dedicated mammographic dry laser imaging system.Material and methodsDigital images of a tissue equivalent breast phantom were obtained using a GE Senographe 2000D digital mammography system and different target/filter combinations of the X-ray tube. These images were printed on films using the Fuji FL-IM D wet laser imaging system and the Kodak DryView 8600 dry laser imaging system. The quality of images was assessed in terms of detectability of microcalcifications and simulated tumour masses by five radiologists. In addition, the contrast index and speed index of the two systems were measured using the step wedge in the phantom. The unpaired, unequal variance t-test was used to test any statistically significant differences.ResultsThere were no significant (p < 0.05) differences between the images printed using the two systems in terms of microcalcification and tumour mass detectability. The wet system resulted in slightly higher contrast index while the dry system showed significantly higher speed index.ConclusionBoth wet and dry laser imaging systems can produce mammography images of good quality on which 0.2 mm microcalcifications and 2 mm tumour masses can be detected. Dry systems are preferable due to the absence of wet chemical processing and solid or liquid chemical waste. The wet laser imaging systems, however, still represent a useful alternative to dry laser imaging systems for mammography studies.     

Storage phosphor versus screen-film radiography: effect of varying exposure parameters and unsharp mask filtering on the detectability of cortical bone defects

Diagnostic performance with storage phosphor radiography is influenced by exposure parameters and digital filtering algorithms. The authors compared the detectability of cortical lesions in excised human femoral shafts on state-of-the-art screen-film radiographs and storage phosphor digital radiographs. For the digital system, the effect of varying exposure parameters (photon flux and tube voltage) and unsharp mask filtering (kernel size and enhancement factor) was tested. Analysis of receiver operating characteristics was performed for 10,560 observations made by eight radiologists. Under identical exposure conditions, storage phosphor imaging yielded no significant advantages over conventional screen-film radiography. Although large variations in exposure dose are possible with storage phosphors, the potential for dose reduction was limited even by means of an increase in tube voltage. The performance with unsharp masked images declined with decreasing kernel size and pronounced enhancement.     

Effects of processing conditions on mammographic image quality

RATIONALE AND OBJECTIVES: Any given mammographic film will exhibit changes in sensitometric response and image resolution as processing variables are altered. Developer type, immersion time, and temperature have been shown to affect the contrast of the mammographic image and thus lesion visibility. The authors evaluated the effect of altering processing variables, including film type, developer type, and immersion time, on the visibility of masses, fibrils, and speaks in a standard mammographic phantom. MATERIALS AND METHODS: Images of a phantom obtained with two screen types (Kodak Min-R and Fuji) and five film types (Kodak Min-R M, Min-R E, Min-R H; Fuji UM-MA HC, and DuPont Microvision-C) were processed with five different developer chemicals (Autex SE, DuPont HSD, Kodak RP, Picker 3-7-90, and White Mountain) at four different immersion times (24, 30, 36, and 46 seconds). Processor chemical activity was monitored with sensitometric strips, and developer temperatures were continuously measured. The film images were reviewed by two board-certified radiologists and two physicists with expertise in mammography quality control and were scored based on the visibility of calcifications, masses, and fibrils. RESULTS: Although the differences in the absolute scores were not large, the Kodak Min-R M and Fuji films exhibited the highest scores, and images developed in White Mountain and Autex chemicals exhibited the highest scores. CONCLUSION: For any film, several processing chemicals may be used to produce images of similar quality. Extended processing may no longer be necessary.