Ex Parte Jack et al

Board of Patent Appeals and Interferences

Feb 7, 2011

10115334 (B.P.A.I. Feb. 7, 2011)

UNITED STATES PATENT AND TRADEMARK OFFICE
__________

BEFORE THE BOARD OF PATENT APPEALS
AND INTERFERENCES
__________

Ex parte CLIFFORD R. JACK and PETER C. O’BRIEN
__________

Appeal 2009-015192
Application 10/115,334
Technology Center 3700
__________

Before DEMETRA J. MILLS, ERIC GRIMES, and JEFFREY N.
FREDMAN, Administrative Patent Judges.

GRIMES, Administrative Patent Judge.

DECISION ON APPEAL1
This is an appeal under 35 U.S.C. § 134 involving claims to a
magnetic resonance imaging (MRI) method. The Examiner has rejected the

1 The two-month time period for filing an appeal or commencing a civil
action, as recited in 37 C.F.R. § 1.304, or for filing a request for rehearing,
as recited in 37 C.F.R. § 41.52, begins to run from the “MAIL DATE”
(paper delivery mode) or the “NOTIFICATION DATE” (electronic delivery
mode) shown on the PTOL-90A cover letter attached to this decision.
Appeal 2009-015192
Application 10/115,334

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claims as being directed to nonstatutory subject matter and obvious in view
of the prior art. We have jurisdiction under 35 U.S.C. § 6(b). We reverse.
STATEMENT OF THE CASE
The Specification discloses a method for “automatically measuring
the volume of tissue in a region of interest by acquiring a magnetic
resonance image, constructing a pixel intensity histogram of the image, and
segmenting the histogram using a statistical regression analysis” (Spec. 5,
¶ 18). The “histogram is produced by counting the number of image pixels
at each possible image intensity level and plotting the result as a frequency
versus intensity graph” (id. at 5, ¶ 20).
Claims 1-34 are on appeal. Claims 1 and 4 are representative and read
as follows:
1. A method of classifying tissue in a magnetic resonance image, the
method comprising:
(a) acquiring a magnetic resonance image of a region of interest;
(b) constructing a pixel intensity histogram of the magnetic resonance
image; and
(c) applying a statistical regression analysis to the histogram to
determine a pixel intensity threshold value for segmenting the histogram into
at least two regions, wherein at least one of the regions is representative of a
tissue of interest.

4. The method as defined in claim 1, wherein the statistical regression
analysis of step (c) comprises:
(i) identifying a consistently identifiable statistical characteristic of the
histogram;
(ii) determining a statistical parameter of the consistently identifiable
statistical characteristic; and
(iii) applying the statistical parameter as an independent variable in a
regression analysis to determine a threshold value to classify pixels based on
pixel signal intensity.

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The claims stand rejected as follows:
• Claims 1-34 under 35 U.S.C. § 101 as being directed to
nonstatutory subject matter (Answer 3);
• Claims 1-13, 15-27, and 29-34 under 35 U.S.C. § 103(a) based on
Nyul2 and Gosche3 (Answer 3); and
• Claims 14 and 28 under 35 U.S.C. § 103(a) based on Nyul, Gosche,
and Komiya4 (Answer 5).
I.
The Examiner has rejected all of the claims on appeal on the basis that
they are directed to nonstatutory subject matter under the machine-or-
transformation test set out by the Court of Appeals for the Federal Circuit in
In re Bilski, 545 F.3d 943 (2008) (Answer 3). The U.S. Supreme Court
subsequently held, however, that while “the machine-or-transformation test
is a useful and important clue” to determining whether a claimed process
passes muster under § 101, it is “not the sole test for deciding whether an
invention is a patent-eligible ‘process.’” Bilski v. Kappos, 130 S.Ct 3218,
3227 (2010).
The Federal Circuit, applying Bilski v. Kappos, noted that the
“Supreme Court has articulated only three exceptions to the Patent Act’s
broad patent-eligibility principles: ‘laws of nature, physical phenomena, and
abstract ideas.’” Research Corporation Technologies, Inc. v. Microsoft
Corp., 627 F.3d 859, 867 (quoting Diamond v. Chakrabarty, 447 U.S. 303,

2 Nyul et al., US 6,584,216, June 24, 2003
3 Gosche, US 6,430,430, Aug. 6, 2002
4 Komiya et al., US 5,754,676, May 19, 1998
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309 (1980)). The Court held that, for a claimed method to be disqualified
under § 101 because it is too abstract, “this disqualifying characteristic
should exhibit itself so manifestly as to override the broad statutory
categories of eligible subject matter.” Id. at 868.
The claims in Research Corporation were directed to methods “for
rendering a halftone image of a digital image by comparing, pixel by pixel,
the digital image against a blue noise mask.” Id. The Research Corporation
court held that the claims at issue there were not directed to abstract ideas.
Id. at 869.
Similar to the Research Corporation claims, the instant claims are
directed to a method for interpreting a magnetic resonance image by
measuring, pixel-by-pixel, the image intensity and statistically analyzing a
frequency-versus-intensity histogram. The Examiner has not alleged that the
claims are directed to a law of nature or physical phenomenon, and we
conclude that the claimed process is not so manifestly abstract as to override
the broad statutory categories of eligible subject matter recited in § 101. See
Research Corporation, 627 F.3d at 868. The rejection of the claims as
directed to nonstatutory subject matter is reversed.
II.
The Examiner has rejected claims 1-13, 15-27, and 29-34 as obvious
based on Nyul and Gosche (Answer 3) and has rejected claims 14 and 28 as
obvious based on Nyul, Gosche, and Komiya. All of the claims on appeal
require using a statistical regression analysis to distinguish between tissue
types based on pixel intensity in an MRI image (see independent claims 1,
11, and 26).
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Appellants argue that Nyul and Gosche do not disclose or suggest a
statistical regression analysis (Appeal Br. 22-23).
The Examiner finds that Nyul discloses statistical regression analysis
at col. 17, ll. 11-37 (Answer 4) and discloses an analysis corresponding to
the steps of claim 4 at column 11 (Answer 9).
We agree with Appellants that the Examiner has not adequately
explained how Nyul and Gosche would have made obvious the statistical
regression analysis required by the claimed method. Appellants dispute the
Examiner’s finding that Nyul discloses statistical regression analysis at
column 17 (Appeal Br. 13). The Examiner concedes that “the references do
not explicitly teach the term ‘regression’” (Answer 10), but does not explain
how Nyul’s column 17 nonetheless discloses statistical regression analysis.
Instead, the Examiner attempts to match Nyul’s disclosure to the steps
recited in dependent claim 4, as follows:
The statistical characteristic of the histogram is the ident-
ification of the landmark points and this is clearly disclosed in
the Nyul reference (see col. 11). The statistical parameter is the
mode and the Nyul reference clearly teaches constructing
unimodal, bimodal and multi-modal histograms. The statistical
thresholding to identify pixels or classify pixels is disclosed in
both Nyul and Gosche references. While the references do not
explicitly teach the term ‘regression’, it [is] obvious that the
references meet the requirements of ‘statistical regression
analysis’ (as defined in the claims . . .).
(Answer 10.)
We cannot agree with the Examiner that it is obvious, based on the
above reasoning, how the identified passage of Nyul describes statistical
regression analysis. Claim 4 describes a statistical regression analysis
encompassed by claim 1, and requires identifying a statistical characteristic
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of a histogram and determining a statistical parameter of that characteristic.
The Examiner’s reasoning does not explain how constructing a unimodal,
bimodal or multi-modal histogram corresponds to determining a statistical
parameter of the landmark points identified by Nyul. Nor has the Examiner
pointed to any step in Nyul corresponding to step (iii) of claim 4: “applying
the statistical parameter as an independent variable in a regression analysis.”
The Specification describes one exemplary method as follows: “[T]he
first step of the segmentation portion 18 of the method comprises identifying
a consistently identifiable statistical characteristic of the histogram which
can be a mean, a median, a mode or other parameters” (Spec. 10-11, ¶ 32).
Then statistical parameters are calculated based on the region of the
histogram near the selected characteristic (e.g., near the mode) (id.) and “the
statistical parameters . . . are used as independent variables in a regression
equation analysis” (id. at 11, ¶ 33).
The Examiner has not pointed to any disclosure in Nyul or Gosche of
using histogram parameters, determined based on a selected characteristic of
the histogram, as independent variables in an analysis that distinguishes
tissue types based on pixel intensity. Nor has the Examiner provided
reasoning sufficient to support a conclusion that such an analysis would have
been obvious based on the cited references. The Examiner therefore has not
adequately shown that Nyul and Gosche, even in combination, would have
made obvious the statistical regression analysis required by the claims on
appeal.
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SUMMARY
We reverse the rejections of claims 1-34 under 35 U.S.C. §§ 101 and
103(a).
REVERSED

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